Preoperative planning and associated intraoperative registration for a surgical system

ABSTRACT

Aspects of the disclosure may involve a method of generating resection plane data for use in planning an arthroplasty procedure on a patient bone. The method may include: obtaining patient data associated with at least a portion of the patient bone, the patient data captured using a medical imaging machine; generating a three-dimensional patient bone model from the patient data, the patient bone model including a polygonal surface mesh; identifying a location of a posterior point on the polygonal surface mesh; creating a three-dimensional shape centered at or near the location; identifying a most posterior vertex of all vertices of the polygonal surface mesh that may be enclosed by the three-dimensional shape; using the most posterior vertex as a factor for determining a posterior resection depth; and generating resection data using the posterior resection depth, the resection data configured to be utilized by a navigation system during the arthroplasty procedure.

TECHNICAL FIELD

The present disclosure relates to medical systems and methods. Morespecifically, the present disclosure relates to preoperative planning ofsurgeries and registering of associated information for use by acomputerized surgical system.

BACKGROUND

Modern orthopedic joint replacement surgery typically involves at leastsome degree of preoperative planning of the surgery in order to increasethe effectiveness and efficiency of the particular procedure. Inparticular, preoperative planning may increase the accuracy of boneresections and implant placement while reducing the overall time of theprocedure and the time the patient joint is open and exposed.

The use of robotic systems in the performance of orthopedic jointreplacement surgery can greatly reduce the intraoperative time of aparticular procedure. Increasingly, the effectiveness of the proceduremay be based on the tools, systems, and methods utilized during thepreoperative planning stages.

Examples of steps involved in preoperative planning may involvedetermining: implant size, position, and orientation; resection planesand depths; access trajectories to the surgical site; and others. Incertain instances, the preoperative plan may involve generating athree-dimensional (“3D”), patient specific, model of the patient bone(s)to undergo the joint replacement. The 3D patient model may be used as avisual aid in planning the various possibilities of implant sizes,implant orientations, implant positions, and corresponding resectionplanes and depths, among other parameters.

While the framework for certain aspects of preoperative planning may beknown in the art, there is a need for tools, systems, and methods tofurther refine certain aspects of preoperative planning to furtherincrease efficiency and effectiveness in robotic and robotic-assistedorthopedic joint replacement surgery.

SUMMARY

Aspects of the present disclosure may involve a method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone. The method may include: obtaining patient data associatedwith at least a portion of the patient bone, the patient data capturedusing a medical imaging machine; generating a three-dimensional patientbone model from the patient data, the patient bone model including apolygonal surface mesh; identifying a location of a posterior point onthe polygonal surface mesh; creating a three-dimensional shape centeredat or near the location; identifying a most posterior vertex of allvertices of the polygonal surface mesh that may be enclosed by thethree-dimensional shape; using the most posterior vertex as a factor fordetermining a posterior resection depth; and generating resection datausing the posterior resection depth, the resection data configured to beutilized by a navigation system during the arthroplasty procedure.

In certain instances, the three-dimensional patient bone model may be athree-dimensional patient femur model.

In certain instances, the method may further include: identifying afirst location of a first posterior point on a first three-dimensionalbone model; and mapping the first location on the firstthree-dimensional bone model to the location on the three-dimensionalpatient bone model. The first location may be positionally correlatedwith the location.

In certain instances, the first three-dimensional bone model may be ageneric bone model.

In certain instances, the three-dimensional shape may include a spherewith a radius of about 7 mm.

In certain instances, the radius may be multiplied by a scaling factor.

In certain instances, the scaling factor may be one of a medial-lateralor anterior-posterior size difference between the three-dimensionalpatient bone model and a generic bone model.

In certain instances, the polygonal surface mesh may be a triangularsurface mesh.

In certain instances, the three-dimensional shape may include a sphere.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone. The method may include: obtaining patient data associatedwith at least a portion of the patient bone, the patient data capturedusing a medical imaging machine; generating a three-dimensional patientbone model from the patient data, the patient bone model including apolygonal surface mesh; identifying a location of a distal point on thepolygonal surface mesh; creating a three-dimensional shape centered ator near the location; identifying a most distal vertex of all verticesof the polygonal surface mesh that are enclosed by the three-dimensionalshape; and determining if the most distal vertex may be too close to aboundary of the three-dimensional shape; using the most distal vertex asa basis for determining a distal resection depth if the most distalvertex may be not too close to the boundary of the three-dimensionalshape; and generating resection data using the distal resection depth,the resection data configured to be utilized by a navigation systemduring the arthroplasty procedure.

In certain instances, the three-dimensional shape may include anellipsoid oriented relative to the three-dimensional patient bone modelsuch that Rx extends medial-lateral, Ry extends anterior-posterior, andRz extends distal-proximal. In certain instances, Rx may be about 7 mm,Ry may be about 10 mm, and Rz may be about 7 mm.

In certain instances, the most distal vertex may be too close to theboundary of the ellipsoid if a location of the most distal vertex may begreater than 0.65 for the ellipsoid function: f=x^2/a^2+y^2/b^2+z^2/c^2,x may be a difference in an x-direction between the first location andthe most distal vertex, y may be a difference in a y-direction betweenthe first location and the most distal vertex, z may be a difference ina z-direction between the first location and the most distal vertex, amay be Rx, b may be Ry, and c may be Rz.

In certain instances, the three-dimensional patient bone model may be athree-dimensional patient femur model.

In certain instances, the three-dimensional shape may include anellipsoid, a sphere, a prism, a cube, or a cylinder.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone. The method may include: obtaining patient data associatedwith at least a portion of the patient bone, the patient data capturedusing a medical imaging machine; generating a three-dimensional patientbone model from the patient data, the patient bone model including apolygonal surface mesh; identifying a location of a distal point on thepolygonal surface mesh; creating a first three-dimensional shapecentered at or near the location; identifying a most distal vertex ofall vertices of the polygonal surface mesh that are enclosed by thefirst three-dimensional shape; determining if the most distal vertex maybe located on an osteophyte; using the most distal vertex or an adjustedlocation of the most distal vertex as a basis for determining a distalresection depth based on whether or not the most distal vertex may belocated on the osteophyte; and generating resection data using thedistal resection depth, the resection data configured to be utilized bya navigation system during the arthroplasty procedure.

In certain instances, determining if the most distal vertex may belocated on an osteophyte may include creating a second three-dimensionalshape positioned between the most distal vertex and the location.

In certain instances, the method may further include identifyingparticular vertices of the polygonal surface mesh that are enclosed bythe second three-dimensional shape, and using information associatedwith the particular vertices to determine if the distal vertex may belocated on an osteophyte.

In certain instances, the information may be a minimum and a maximumvalue in a direction associated with a presence of an osteophyteprotruding from an articular surface.

In certain instances, the method may further include identifyingparticular vertices of the polygonal surface mesh that are enclosed bythe second three-dimensional shape, and using a minimum vertex value ofone of the particular vertices enclosed by the second three-dimensionalshape in a certain coordinate direction and a maximum vertex value ofanother one of the particular vertices enclosed by the secondthree-dimensional shape in the certain coordinate direction to determineif the distal vertex may be located on an osteophyte.

In certain instances, the method may further include determining thedifference between the maximum vertex value and the minimum vertexvalue, and using the difference to determine the presence of anosteophyte.

In certain instances, the second three-dimensional shape may include asphere having a radius of about 2 mm and may be centered 1 mm towardsthe location from the most distal vertex.

In certain instances, the method may further include identifyingparticular vertices of the polygonal surface mesh that are enclosed by aboundary of the sphere, and determining a difference between a maximumvertex value of one of the particular vertices enclosed by the boundaryin a certain coordinate direction and a minimum vertex value of anotherone of the particular vertices enclosed by the boundary in the certaincoordinate direction.

In certain instances, the method may further include using thedifference to determine whether to increase or decrease a size of thesphere.

In certain instances, the first three-dimensional shape may include anellipsoid. In certain instances, the second three-dimensional shape mayinclude a sphere.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone. The method may include: obtaining patient data associatedwith at least a portion of the patient bone; generating athree-dimensional patient bone model from the patient data, the patientbone model oriented in a three-dimensional coordinate system andincluding a polygonal surface mesh; identifying a particular directionin the three-dimensional coordinate system associated with a resectionplane; identifying a location on the polygonal surface mesh; creating asurface at or near the location; identifying a particular vertex of allvertices of the polygonal surface mesh that extends furthest beyond thesurface in the particular direction; using the particular vertex as afactor for determining a particular resection depth; and generatingresection data using the particular resection depth, the particularresection data configured to be utilized by a navigation system duringthe arthroplasty procedure.

In certain instances, the surface may be a plane.

In certain instances, the surface may be a three-dimensional shape. Incertain instances, the three-dimensional shape may be a sphere,ellipsoid, prism, or cube.

In certain instances, the method may further include identifying a firstlocation of a first posterior point on a first three-dimensional bonemodel; and mapping the first location on the first three-dimensionalbone model to the location on the three-dimensional patient bone model.The first location may be positionally correlated with the location.

In certain instances, the first three-dimensional bone model may be ageneric bone model.

In certain instances, the surface may include a sphere with a radius ofabout 7 mm. In certain instances, the radius may be multiplied by ascaling factor. In certain instances, the scaling factor may be one of amedial-lateral or anterior-posterior size difference between thethree-dimensional patient bone model and a generic bone model.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection plane and checkpoint positioning data for use in planning anarthroplasty procedure on a patient bone. The method may include:obtaining patient data associated with at least a portion of the patientbone, the patient data captured using a medical imaging machine;generating a three-dimensional patient bone model from the patient data,the patient bone model including a polygonal surface mesh; identifying afirst location of a first checkpoint on the patient bone model;identifying a second location of a resection plane relative to thepatient bone model, the resection plane defining a resection surface onthe patient bone model to be exposed following a resection; determininga shortest signed distance vector from the first location to a point onthe resection surface; using information associated with the shortestsigned distance vector to determine if the first location of the firstcheckpoint may be located too close to the second location of theresection plane; and

generating resection and checkpoint positioning data using theinformation, the resection and checkpoint positioning data configured tobe utilized by a navigation system during the arthroplasty procedure.

In certain instances, the method may further include identifying anormal line for the resection surface, the normal line extending awayfrom the patient bone model and perpendicular to the resection surface.

In certain instances, the method may further include determining thefirst location of the first checkpoint may be located too close to thesecond location of the resection plane when the normal line and theshortest signed distance vector point in opposite directions.

In certain instances, the patient bone model may be a femur bone model.In certain instances, the patient bone model may be a tibial bone model.

In certain instances, the method may further include determining thecheckpoint may be located too close to the resection plane when: thenormal line and the shortest signed distance vector point in a samedirection, and a magnitude of the shortest signed distance vector may beless than or equal to about 4.50 mm.

In certain instances, the patient bone model may be a femur bone model.In certain instances, the patient bone model may be a tibial bone model.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingimplant position and orientation data for use in planning anarthroplasty procedure on a patient bone including a lateral femur area,proximal femur area, and a posterior femur area. The method may include:obtaining patient data associated with at least a portion of the patientbone; generating a three-dimensional patient femur model from thepatient data, the patient femur model including a surface boundary and acortex region, the patient femur model being in a three-dimensionalcoordinate system with an X-axis in a medial-lateral direction, a Y-axisin an anterior-posterior direction with the +Y-axis pointing towards theposterior femur area, and a Z-axis in a superior-inferior direction withthe +Z axis pointing towards the proximal femur area; obtaining athree-dimensional femoral implant model including an anterior flangeportion having a superior edge and an anterior bone resection contactsurface being planar and adjacent the superior edge; determining aposition and orientation of the femoral implant model relative to thepatient femur model; extending a haptic plane coplanar with the anteriorbone resection contact surface, the haptic plane including a superiorboundary positioned superior of the superior edge of the anterior flangeportion of the femoral implant model; identifying a series of points onthe superior boundary of the haptic plane; projecting a vector along theY-axis from each of the series of points to a corresponding surface ofthe surface boundary of the patient femur model; determining thatnotching occurs based on a length and a direction of a smallest of thevectors; and generating implant component position and orientation databased on the determined position and orientation of the femoral implantmodel relative to the patient femur model, the implant componentposition and orientation data configured to be utilized by a navigationsystem during the arthroplasty procedure.

In certain instances, notching occurs when: the length of the smallestof the vectors may be equal to or greater than 0 mm; and the directionof the smallest of the vectors may be opposite of the +Y-axis of thecoordinate system.

In certain instances, no notching occurs when: the length of thesmallest of the vectors may be greater than 0 mm; and the direction ofthe smallest of the vectors may be in a same direction as the +Y-axis ofthe coordinate system.

In certain instances, the length may be based on a perceivable depth ofnotching.

In certain instances, the series of points are equally spaced along thesuperior boundary of the haptic plane. In certain instances, the seriesof points are equally spaced based upon a radius of curvature at or nearthe cortex region of the patient femur model. In certain instances, theseries of points are equally spaced based upon a clinically relevantdepth of perceivable notching. In certain instances, the series ofpoints are equally spaced based upon: a radius of curvature at or nearthe cortex region of the patient femur model; and a clinically relevantdepth of perceivable notching. In certain instances, the series ofpoints are equally spaced about 3.15 mm apart.

In certain instances, the patient data may be captured using a medicalimaging machine.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingimplant position and orientation data for use in planning anarthroplasty procedure on a patient bone including a lateral femur area,proximal femur area, and a posterior femur area. The method may include:obtaining patient data associated with at least a portion of the patientbone, the patient data captured using a medical imaging machine;generating a three-dimensional patient femur model from the patientdata; obtaining a three-dimensional femoral implant model including ananterior flange portion having an associated haptic resection objecthaving a superior boundary edge; determining a position and orientationof the femoral implant model relative to the patient femur model;determining that notching occurs based on an intersection of thesuperior boundary edge and the three-dimensional patient femur model;and generating implant component position and orientation data based onthe determined position and orientation of the femoral implant modelrelative to the patient femur model, the implant component position andorientation data configured to be utilized by a navigation system duringthe arthroplasty procedure.

In certain instances, the three-dimensional patient femur model mayinclude a surface boundary and a cortex region, the patient femur modelbeing in a three-dimensional coordinate system with an X-axis in amedial-lateral direction, a Y-axis in an anterior-posterior directionwith the +Y-axis pointing towards the posterior femur area, and a Z-axisin a superior-inferior direction with the +Z axis pointing towards theproximal femur area; the method further including: identifying a seriesof points on the superior boundary edge of the haptic resection object;projecting a vector along the Y-axis from each of the series of pointsto a corresponding surface of the surface boundary of the patient femurmodel; and determining that notching occurs based on a length and adirection of a smallest of the vectors.

In certain instances, notching occurs when: the length of the smallestof the vectors may be equal to or greater than 0 mm; and the directionof the smallest of the vectors may be opposite of the +Y-axis of thecoordinate system.

In certain instances, no notching occurs when: the length of thesmallest of the vectors may be greater than 0 mm; and the direction ofthe smallest of the vectors may be in a same direction as the +Y-axis ofthe coordinate system.

In certain instances, the length may be based on a perceivable depth ofnotching.

In certain instances, the series of points are equally spaced along thesuperior boundary edge. In certain instances, the series of points areequally spaced based upon a radius of curvature at or near the cortexregion of the patient femur model. In certain instances, the series ofpoints are equally spaced based upon a clinically relevant depth ofperceivable notching. In certain instances, the series of points areequally spaced based upon: a radius of curvature at or near the cortexregion of the patient femur model; and a clinically relevant depth ofperceivable notching. In certain instances, the series of points areequally spaced about 3.15 mm apart.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection data for use in planning an arthroplasty procedure on apatient bone covered at least partially in cartilage. The method mayinclude: receiving a three-dimensional patient bone model including abone model surface, the three-dimensional patient bone model correlatedwith a position and orientation of the patient bone via a navigationsystem, the three-dimensional patient bone model in a three-dimensionalcoordinate system; identifying a target region on the bone model surfaceof the three-dimensional patient bone model for intra-operativeregistration; receiving location data for a first plurality of pointsbased on the intra-operative registration of the cartilage on thepatient bone in locations corresponding to points within the targetregion on the bone model surface of the three-dimensional bone model;determining a resection depth based at least in part on the locationdata for the first plurality of point; and generating resection datausing the resection depth, the resection data configured to be utilizedby the navigation system during the arthroplasty procedure.

In certain instances, the method may further include mapping thelocation data for the first plurality of points into thethree-dimensional coordinate system.

In certain instances, determining the resection depth may includedetermining a depth difference between the first plurality of points andthe target region on the bone model surface.

In certain instances, the method may further include determining theresection depth by adding the depth difference to a bone-only resectiondepth.

In certain instances, the bone-only resection depth may be adjusteddistally by the addition of the depth difference.

In certain instances, determining the resection depth may includealtering a bone-only resection depth based on the first plurality ofpoints.

In certain instances, the bone-only resection depth may be adjusteddistally based on the first plurality of points.

In certain instances, the patient bone may include a femur and thethree-dimensional patient bone model may include a three-dimensionalpatient femur model.

In certain instances, the target region may include an articular area ofat least one of a medial or lateral condyle of the three-dimensionalpatient femur model.

In certain instances, the patient bone may include a tibia and thethree-dimensional patient bone model may include a three-dimensionalpatient tibia model.

In certain instances, the resection depth may include a proximalresection depth of the tibia, the proximal resection depth may beadjusted proximally based on the location data for the first pluralityof points.

In certain instances, the target region may include an articular area ofat least one of a medial or lateral tibial plateau of thethree-dimensional patient tibia model.

In certain instances, the three-dimensional patient bone model may be abone only model.

In certain instances, the three-dimensional patient bone model may begenerated from medical images of the patient bone.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection data for use in planning an arthroplasty procedure on a kneejoint including a femur and a tibia of a patient. The method mayinclude: receiving a three-dimensional femur model and athree-dimensional femur implant model oriented relative to each other ina first pre-planned orientation in a common three-dimensional coordinatesystem, the three-dimensional femur model corresponding to the femur ofthe patient, the three-dimensional femur implant model including amedial condyle surface and a lateral condyle surface; receiving athree-dimensional tibia model and a three-dimensional tibia implantmodel oriented relative to each other in a second pre-plannedorientation in the common three-dimensional coordinate system, thethree-dimensional tibia model corresponding to the tibia of the patient,the three-dimensional tibia implant model including a medial articularsurface and a lateral articular surface, the three-dimensional femurmodel and the three-dimensional tibia model oriented relative to eachother according to a pose of the femur and tibia of the patient via anavigation system; receiving first position and orientation datacorresponding to a first position and orientation of the femur and thetibia in a first pose; calculating a first signed distance between themedial condyle surface of the three-dimensional femur implant model anda first point on or associated with the three-dimensional tibia implantmodel in the first pose; calculating a second signed distance betweenthe lateral condyle surface of the three-dimensional femur implant modeland a second point on or associated with the three-dimensional tibiaimplant model in the first pose; determining or adjusting a resectiondepth based on the first and second signed distances; and generatingresection data using the resection depth, the resection data configuredto be utilized by the navigation system during the arthroplastyprocedure.

In certain instances, the three-dimensional femur model and thethree-dimensional tibia model are generated from medical images of theknee joint of the patient.

In certain instances, the first pose may be with the knee joint inextension.

In certain instances, the first point may be on the medial articularsurface of the three-dimensional tibia implant model, and the secondpoint may be on the lateral articular surface of the three-dimensionaltibia implant model.

In certain instances, the first and second signed distances arecalculated via a global search closest distance algorithm.

In certain instances, the global search closest distance algorithmidentifies a reference vertex associated with each of the medial andlateral condyle surfaces and the medial and lateral articular surfaces.

In certain instances, the method may further include: receiving secondposition and orientation data corresponding to a second position andorientation of the femur and the tibia in a second pose that may bedifferent than the first pose; calculating a third signed distancebetween the medial condyle surface of the three-dimensional femurimplant model and the medial articular surface of the three-dimensionaltibia implant model in the second pose; and calculating a fourth signeddistance between the lateral condyle surface of the three-dimensionalfemur implant model and the lateral articular surface of thethree-dimensional tibia implant model in the second pose.

In certain instances, the second pose may be flexion.

In certain instances, the first, second, third, and fourth signeddistances are calculated via a global search closest distance algorithm.

In certain instances, the first and second signed distances arecalculated via a global search closest distance algorithm, and the thirdand fourth signed distances are calculated via an incremental searchclosest distance algorithm.

In certain instances, the global search closest distance algorithmidentifies a reference vertex associated with each of the medial andlateral condyle surfaces and the medial and lateral articular surfaces,and the incremental search closest distance algorithm may be utilizedfor particular vertexes that are adjacent the reference vertexes of themedial and lateral condyle surfaces to determine if any of theparticular vertexes are closer to the corresponding medial or lateralarticular surface, respectively, than the reference vertexes.

In certain instances, the three-dimensional femur implant model mayinclude a first triangular surface mesh including vertexes, thethree-dimensional tibia implant model including a second triangularsurface mesh including faces, the first and second signed distances arecalculated between the vertexes of the three-dimensional femur implantmodel and the faces of the three-dimensional tibia implant model.

In certain instances, the medial and lateral articular surfaces of thethree-dimensional tibia implant model are modified to be flatter or lessconcave for determining the resection depth as compared with medial andarticular surfaces of a physical tibial implant to be employed in thearthroplasty procedure.

In certain instances, the first point may be on a medial portion of atibial resection plane associated with the three-dimensional tibiaimplant model, and the second point may be on a lateral portion of thetibial resection plane associated with the three-dimensional tibiaimplant model.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

Aspects of the present disclosure may involve a method of generatingresection data for use in planning an arthroplasty procedure on a jointformed by a first bone and a second bone of the patient. The method mayinclude: receiving a first three-dimensional bone model and a firstthree-dimensional implant model oriented relative to each other in afirst pre-planned orientation in a common three-dimensional coordinatesystem, the first three-dimensional bone model corresponding to thefirst bone of the patient, the first three-dimensional implant modelincluding a first implant articular surface; receiving a secondthree-dimensional bone model and a second three-dimensional implantmodel oriented relative to each other in a second pre-plannedorientation in the common three-dimensional coordinate system, thesecond three-dimensional bone model corresponding to the second bone ofthe patient, the second three-dimensional implant model including asecond implant articular surface, the first three-dimensional bone modeland the second three-dimensional bone model oriented relative to eachother according to a pose of the first bone and the second bone of thepatient via a navigation system; receiving first position andorientation data corresponding to a first position and orientation ofthe first bone and the second bone in a first pose; calculating a firstsigned distance between the first implant articular surface of the firstthree-dimensional implant model and a first point on or associated withthe second three-dimensional implant model in the first pose;determining or adjusting a resection depth based on the first distance;and generating resection data using the resection depth, the resectiondata configured to be utilized by the navigation system during thearthroplasty procedure.

In certain instances, the joint may be one of a knee, ankle, elbow, orwrist.

In certain instances, the first bone may be a femur and the second bonemay be a tibia.

In certain instances, the first point may be on a portion of a proximaltibial resection plane associated with the second three-dimensionalimplant model.

In certain instances, the first three-dimensional implant model mayinclude a medial condyle surface and a lateral condyle surface, thesecond three-dimensional implant model may include a medial articularsurface and a lateral articular surface, the first signed distancedetermined between the medial condyle surface and the first point.

In certain instances, the method may further include calculating asecond signed distance between the lateral condyle surface and a secondpoint on or associated with the second three-dimensional implant modelin the first pose.

In certain instances, the first point may be on the medial articularsurface of the second three-dimensional implant model, and the secondpoint may be on the lateral articular surface of the secondthree-dimensional implant model.

In certain instances, the medial and lateral articular surfaces of thesecond three-dimensional implant model are modified to be flatter orless concave for determining the resection depth as compared with medialand articular surfaces of a physical implant to be employed in thearthroplasty procedure.

In certain instances, the first and second signed distances arecalculated via a global search closest distance algorithm.

In certain instances, the global search closest distance algorithmidentifies a reference vertex associated with each of the medial andlateral condyle surfaces and the medial and lateral articular surfaces.

In certain instances, the method may further include: receiving secondposition and orientation data corresponding to a second position andorientation of the first bone and the second bone in a second pose thatmay be different than the first pose; calculating a third signeddistance between the medial condyle surface of the firstthree-dimensional implant model and the medial articular surface of thesecond three-dimensional implant model in the second pose; andcalculating a fourth signed distance between the lateral condyle surfaceof the first three-dimensional implant model and the lateral articularsurface of the second three-dimensional implant model in the secondpose.

In certain instances, the first, second, third, and fourth signeddistances are calculated via a global search closest distance algorithm.

In certain instances, the first and second signed distances arecalculated via a global search closest distance algorithm, and the thirdand fourth signed distances are calculated via an incremental searchclosest distance algorithm.

In certain instances, the global search closest distance algorithmidentifies a reference vertex associated with each of the medial andlateral condyle surfaces and the medial and lateral articular surfaces,and the incremental search closest distance algorithm may be utilizedfor particular vertexes that are adjacent the reference vertexes of themedial and lateral condyle surfaces to determine if any of theparticular vertexes are closer to the corresponding medial or lateralarticular surface, respectively, than the reference vertexes.

In certain instances, the navigation system operates in conjunction withan autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.

While multiple embodiments are disclosed, still other embodiments of thepresent disclosure will become apparent to those skilled in the art fromthe following detailed description, which shows and describesillustrative embodiments of the disclosure. As will be realized, theembodiments discussed herein are capable of modifications in variousaspects, all without departing from the spirit and scope of the presentdisclosure. Accordingly, the drawings and detailed description are to beregarded as illustrative in nature and not restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustration of a surgical system.

FIG. 2 is a flow chart illustrating surgical planning and performance ofan arthroplasty.

FIGS. 3A and 3B illustrate haptic guidance during performance of anarthroplasty.

FIGS. 4A and 4B respectively illustrate three dimensional computermodels of a proximal end of a generic tibia and a distal end of ageneric femur wherein each three dimensional model is represents astatistical average of its respective bone type according to both sizeand shape.

FIGS. 5A-5C respectively illustrate coronal, axial or transverse, andsagittal views of the proximal end of the three dimensional computermodel of the patient tibia (i.e., the patient tibia model).

FIGS. 6A-6C respectively illustrate coronal, axial or transverse, andsagittal views of the distal end of the three dimensional computer modelof the patient femur (i.e., patient femur model).

FIG. 7 is an enlarged view of a triangular surface mesh of a posteriorcondylar region of a three dimensional patient femur computer model andillustrating a method of adjusting the location of posterior points onthe patient femur model that were mapped onto the patient femur modelfrom a three dimensional generic femur computer model.

FIG. 8 is a flow chart illustrating the method of adjusting theplacement of the mapped posterior points on the patient femur model.

FIG. 9A is an enlarged view of a triangular surface mesh of a distalcondylar region of a three dimensional patient femur computer model andillustrating a method of adjusting the location of distal points on thepatient femur model that were mapped onto the patient femur model from athree dimensional generic femur computer model.

FIG. 9B is an enlarged isometric view of the ellipsoid employed in FIG.9A.

FIG. 9C is the same ellipsoid of FIGS. 9A and 9B plus a sphere employedin the process of fine-tuning the placement of the mapped distal points.

FIGS. 10A-10C is a flow chart outlining the method of adjusting theplacement of the mapped distal points on the patient femur model, thedistal points having been mapped from the generic femur model to thecondyles of the patient femur model.

FIG. 11 is a distal-anterior view of a three dimensional computer modelof the candidate tibial implant (i.e., the tibial implant model)illustrating its bone resection contacting surface distally opposite itstibial plateau.

FIGS. 12A-12C respectively illustrate coronal, axial or transverse, andsagittal views of the tibial implant model superimposed on the proximalend of the three dimensional computer model of the patient tibia (i.e.,the patient tibia model).

FIG. 13 is a sagittal view of a three dimensional computer model of thecandidate femur implant (i.e., the femur implant model) illustrating itsdistal bone resection contacting surface along with the adjacentanterior chamfer resection contacting surface, posterior chamferresection contacting surface, anterior resection contacting surface, andposterior resection contacting surface, these resection contactingsurfaces being proximal the medial and lateral condylar surfaces of theof the femur implant model.

FIGS. 14A-14C respectively illustrate coronal, axial or transverse, andsagittal views of the femur implant model superimposed on the distal endof the three dimensional computer model of the patient femur (i.e., thepatient femur model).

FIGS. 15A-15C are various views of the tibia model as proposed to beresected and illustrating the proposed tibial resection.

FIGS. 16A-16C are various views of the femur model as proposed to beresected and illustrating the proposed femur resections, including thedistal resection.

FIG. 17 is an isometric view of the femoral articular surface of thefemur implant model and the tibial articular surface of the tibialimplant model.

FIGS. 18 and 19 are, respectively, algorithm flow charts of abroad-phase search stage and a narrow-phase search stage of a globalsearch closest distance algorithm.

FIGS. 20A and 20B are, respectively, an anterior distal view and asagittal cross sectional view of the femoral implant model positioned onthe patient femur model such that the anterior femoral cortex isnotched.

FIG. 21 illustrates a coordinate system established for the patientfemur model.

FIGS. 22A-22C are, respectively, posterior, sagittal-posterior, andsagittal views of a candidate femoral implant model with an outline of ahaptic plane superimposed on the femoral implant model.

FIG. 23 is an enlarged anterior view of a superior edge of the anteriorflange portion of the femoral implant model and a superior boundary ofthe haptic plane, a series of equally-spaced reference points extendingalong the superior boundary of the haptic plane.

FIG. 24 is a schematic depiction of an anterior femoral cortex notchsituation.

FIGS. 25A and 25B are cross-sectional sagittal views of the patientfemur model and the candidate femoral implant model thereon inno-notching and notching arrangements, respectively.

FIG. 26A is a side view of a checkpoint used in an intraoperativeregistration process.

FIG. 26B is a side view of a knee joint having a checkpoint positionedon the femur with a navigation probe contacting the checkpoint.

FIG. 26C illustrates a coronal view of a femur implant modelsuperimposed on the distal end of the three dimensional computer modelof the patient femur (i.e., the patient femur model) with a checkpointpositioned on the patient femur model.

FIG. 26D illustrates a coronal view of a tibial implant modelsuperimposed on the proximal end of the three dimensional computer modelof the patient tibia (i.e., the patient tibia model) with a checkpointpositioned on the patient tibia model.

FIG. 26E illustrates steps in a checkpoint location verificationprocess.

FIG. 26F is a sagittal view of the femur and tibial resection planeswith the resection planes sitting “deep” with respect to the checkpoint.

FIG. 26G is a sagittal view of the femur and tibial resection planeswith the resection plane sitting “proud” with respect to the checkpoint.

FIG. 26H is a table illustrating errors associated with the variousresections.

FIG. 26I is a sagittal view of the femur resection planes showing theeffect of anterior chamfer error due to the error in the posteriorresection.

FIG. 26J is a sagittal view of the femur resection planes showing theeffect of anterior chamfer error due to the error in the distalresection.

FIGS. 27A and 27B which are, respectively, a sagittal view of thefemoral implant and patient bone models as preoperatively planned and asagittal view of the tibial implant and patient bone models aspreoperatively planned.

FIGS. 28A and 28B are, respectively, an axial or transverse view and aposterior view of the patient femoral model as depicted on the displayof the system in FIG. 1.

FIGS. 29A and 29B are, respectively, enlarged views of the landmarkcapture regions of FIGS. 28A and 28B, respectively, wherein a series ofregistration points are depicted on each capture region.

FIG. 30 is an example computing system having one or more computingunits that may implement various systems and methods discussed herein isprovided.

DETAILED DESCRIPTION

Preoperative planning of arthroplasty surgical procedures for executionvia a surgical system 100 is disclosed herein. The preoperative planningincludes defining bone resection depths and identifying whether or notunacceptable notching of the femoral anterior cortex is associated withthe proposed bone resection depths and proposed pose of the candidateimplants. Assuming the preoperatively planned bone resection depths andimplant poses are free of unacceptable notching of the femoral anteriorcortex and approved by the surgeon, the bone resection depths can beupdated to account for cartilage thickness by intraoperativelyregistering the cartilage condylar surfaces of the actual patient bonesto the patient bone models employed in the preoperative planning. By soaccounting for the cartilage thickness, the actual implants, uponimplantation via the surgical system 100, will have their respectivecondylar surfaces located so as to act in place of the resectedcartilage condylar surfaces of the actual patient bones.

Before beginning a detailed discussion of the preoperative planning andthe intraoperative registering of the cartilage condylar surface, anoverview of the surgical system and its operation will now be given asfollows.

I. Overview of Surgical System

To begin a detailed discussion of the surgical system, reference is madeto FIG. 1. As can be understood from FIG. 1, the surgical system 100includes a navigation system 42, a computer 50, and a haptic device 60.The navigation system tracks the patient's bone (i.e., tibia 10, femur11), as well as surgical tools (e.g., pointer device, probe, cuttingtool) utilized during the surgery, to allow the surgeon to visualize thebone and tools on a display 56 during the osteotomy procedure.

The navigation system 42 may be any type of navigation system configuredto track the pose (i.e. position and orientation) of a bone. Forexample, the navigation system 42 may include a non-mechanical trackingsystem, a mechanical tracking system, or any combination ofnon-mechanical and mechanical tracking systems. The navigation system 42includes a detection device 44 that obtains a pose of an object withrespect to a coordinate frame of reference of the detection device 44.As the object moves in the coordinate frame of reference, the detectiondevice tracks the pose of the object to detect movement of the object.

In one embodiment, the navigation system 42 includes a non-mechanicaltracking system as shown in FIG. 1. The non-mechanical tracking systemis an optical tracking system with a detection device 44 and a trackableelement (e.g. navigation marker 46) that is disposed on a tracked objectand is detectable by the detection device 44. In one embodiment, thedetection device 44 includes a visible light-based detector, such as aMicronTracker (Claron Technology Inc., Toronto, Canada), that detects apattern (e.g., a checkerboard pattern) on a trackable element. Inanother embodiment, the detection device 44 includes a stereo camerapair sensitive to infrared radiation and positionable in an operatingroom where the arthroplasty procedure will be performed. The trackableelement is affixed to the tracked object in a secure and stable mannerand includes an array of markers having a known geometric relationshipto the tracked object. As is known, the trackable elements may be active(e.g., light emitting diodes or LEDs) or passive (e.g., reflectivespheres, a checkerboard pattern, etc.) and have a unique geometry (e.g.,a unique geometric arrangement of the markers) or, in the case ofactive, wired or wireless markers, a unique firing pattern. Inoperation, the detection device 44 detects positions of the trackableelements, and the surgical system 100 (e.g., the detection device 44using embedded electronics) calculates a pose of the tracked objectbased on the trackable elements' positions, unique geometry, and knowngeometric relationship to the tracked object. The tracking system 42includes a trackable element for each object the user desires to track,such as the navigation marker 46 located on the bone 10. Duringhaptically guided robotic-assisted surgeries, the navigation system mayfurther include a haptic device marker 48 (to track a global or grossposition of the haptic device 60), an end effector marker 54 (to track adistal end of the haptic device 60), and a free-hand navigation probe 55for use in the registration process.

As indicated in FIG. 1, the surgical system 100 further includes aprocessing circuit, represented in the figures as a computer 50. Theprocessing circuit includes a processor and memory device. The processorcan be implemented as a general purpose processor, an applicationspecific integrated circuit (ASIC), one or more field programmable gatearrays (FPGAs), a group of processing components, a purpose-specificprocessor, or other suitable electronic processing components. Thememory device (e.g., memory, memory unit, storage device, etc.) is oneor more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.)for storing data and/or computer code for completing or facilitating thevarious processes, layers and functions described in the presentapplication. The memory device may be or include volatile memory ornon-volatile memory. The memory device may include database components,object code components, script components, or any other type ofinformation structure for supporting the various activities andinformation structures described in the present application. Accordingto an exemplary embodiment, the memory device is communicably connectedto the processor via the processing circuit and includes computer codefor executing (e.g., by the processing circuit and/or processor) one ormore processes described herein.

The computer 50 is configured to communicate with the navigation system42 and the haptic device 60. Furthermore, the computer 50 may receiveinformation related to osteotomy procedures and perform variousfunctions related to performance of osteotomy procedures. For example,the computer 50 may have software as necessary to perform functionsrelated to image analysis, surgical planning, registration, navigation,image guidance, and haptic guidance. More particularly, the navigationsystem may operate in conjunction with an autonomous robot or asurgeon-assisted device (haptic device) in performing the arthroplastyprocedure.

The computer 50 receives images of the patient's anatomy on which anarthroplasty procedure is to be performed. Referring to FIG. 2, prior toperformance of an arthroplasty, the patient's anatomy is scanned usingany known imaging technique, such as CT or MRI (Step 801) captured witha medical imaging machine. And while the disclosure makes reference tomedical images captured or generated with a medical imaging machine suchas a CT or MRI machine, other methods of generating the medical imagesare possible and contemplated herein. For example, an image of the bonemay be generated intra-operatively via a medical imaging machine such asa hand-held scanning or imaging device that scans or registers thetopography of the bone surface. Thus, the term medical imaging machineis intended to encompass relatively large devices located at imagingcenters as well as hand-held imaging devices used intra-operatively.

Continuing on, the scan data is then segmented to obtain athree-dimensional representation of the patient's anatomy. For example,prior to performance of a knee arthroplasty, a three-dimensionalrepresentation of the femur and tibia is created. Using thethree-dimensional representation and as part of the planning process,femoral and tibial landmarks can be selected, and the patient'sfemoral-tibial alignment is calculated along with the orientation andplacement of the proposed femoral and tibial implants, which may beselected as to model and size via the computer 50. The femoral andtibial landmarks may include the femoral head center, the distaltrochlear groove, the center of intercondylar eminence, the tibia-anklecenter, and the medial tibial spine, among others. The femoral-tibialalignment is the angle between the femur mechanical axis (i.e., linefrom femoral head center to distal trochlear groove) and the tibialmechanical axis (i.e., line from ankle center to intercondylar eminencecenter). Based on the patient's current femoral-tibial alignment and thedesired femoral-tibial alignment to be achieved by the arthroplastyprocedure and further including the size, model and placement of theproposed femoral and tibial implants, including the desired extension,varus-valgus angle, and internal-external rotation associated with theimplantation of the proposed implants, the computer 50 is programmed tocalculate the desired implantation of the proposed implants or at leastassist in the preoperative planning of the implantation of the proposedimplants, including the resections to be made via the haptic device 60in the process of performing the arthroplasty procedure (Step 803). Thepreoperative plan achieved via Step 803 is provided to the surgeon forreview, adjustment and approval, and the preoperative plan is updated asdirected by the surgeon (Step 802).

Since the computer 50 is used to develop a surgical plan according toStep 803, it should be understood that a user can interact with thecomputer 50 at any stage during surgical planning to input informationand modify any portion of the surgical plan. The surgical plan includesa plurality of planned virtual boundaries. The virtual boundaries canrepresent holes and/or cuts to be made in a bone 10, 11 during anarthroplasty procedure. Once the surgical plan has been developed, ahaptic device 60 is used to assist a user in creating the planned holesand cuts in the bones 10, 11. Preoperative planning, especially withrespect to bone resection depth planning and the prevention of femoralanterior shaft notching, will be explained more fully below.

The drilling of holes and creation of cuts or resections in bones 10, 11can be accomplished with the assistance of a haptically guidedinteractive robotic system, such as the haptic guidance system describedin U.S. Pat. No. 8,010,180, titled “Haptic Guidance System and Method,”granted Aug. 30, 2011, and hereby incorporated by reference herein inits entirety. As the surgeon manipulates a robotic arm to drill holes inthe bone or perform cuts with a high speed drill, sagittal saw, or othersuitable tool, the system provides haptic feedback to guide the surgeonin sculpting the holes and cuts into the appropriate shape, which ispre-programmed into the control system of the robotic arm. Hapticguidance and feedback will be explained more fully below.

During surgical planning, the computer 50 further receives informationrelated to femoral and tibial implants to be implanted during thearthroplasty procedure. For example, a user may input parameters ofselected femoral and tibial implants into the computer 50 using theinput device 52 (e.g. keyboard, mouse, etc.). Alternatively, thecomputer 50 may contain a pre-established database of various implantsand their parameters, and a user can choose the selected implants fromthe database. In a still further embodiment, the implants may be customdesigned based on a patient-specific surgical plan. Selection of theimplants may occur during any stage of surgical planning

The surgical plan may further be based on at least one parameter of theimplants or a function of a parameter of the implants. Because theimplants can be selected at any stage of the surgical planning process,the implants may be selected prior to or after determination of theplanned virtual boundaries by the computer 50. If the implants areselected first, the planned virtual boundaries may be based at least inpart on a parameter of the implants. For example, the distance (or anyother relationship) between the planned virtual boundaries representingholes or cuts to made in the bones 10, 11 may be planned based on thedesired varus-valgus femoral-tibial alignment, extension,internal-external rotation, or any other factors associated with adesired surgical outcome of the implantation of the arthroplastyimplants. In this manner, implementation of the surgical plan willresult in proper alignment of the resected bone surfaces and holes toallow the selected implants to achieve the desired surgical outcome.Alternatively, the computer 50 may develop the surgical plan, includingthe planned virtual boundaries, prior to implant selection. In thiscase, the implant may be selected (e.g. input, chosen, or designed)based at least in part on the planned virtual boundaries. For example,the implants can be selected based on the planned virtual boundariessuch that execution of the surgical plan will result in proper alignmentof the resected bone surfaces and holes to allow the selected implantsto achieve the desired surgical outcome.

The virtual boundaries exist in virtual space and can be representativeof features existing or to be created in physical (i.e. real) space.Virtual boundaries correspond to working boundaries in physical spacethat are capable of interacting with objects in physical space. Forexample, working boundaries can interact with a surgical tool 58 coupledto haptic device 60. Although the surgical plan is often describedherein to include virtual boundaries representing holes and resections,the surgical plan may include virtual boundaries representing othermodifications to a bone 10, 11. Furthermore, virtual boundaries maycorrespond to any working boundary in physical space capable ofinteracting with objects in physical space.

Referring again to FIG. 2, after surgical planning and prior toperforming an arthroplasty procedure, the physical anatomy (e.g. bones10, 11) is registered to a virtual representation of the anatomy (e.g. apreoperative three-dimensional representation) using any knownregistration technique (Step 804). Possible registration techniquesinclude the point-based registration technique described inabove-referenced U.S. Pat. No. 8,010,180, or 2D/3D registrationutilizing a hand-held radiographic imaging device as described in U.S.application Ser. No. 13/562,163, titled “Radiographic Imaging Device,”filed Jul. 30, 2012, and hereby incorporated by reference herein in itsentirety. Registration of the patient's anatomy allows for accuratenavigation during the surgical procedure (Step 805), which enables eachof the virtual boundaries to correspond to a working boundary inphysical space. For example, referring to FIGS. 3A and 3B, a virtualboundary 62 representing a resection in a tibia bone 10 is displayed ona computer or other display 63 and the virtual boundary 62 correspondsto a working boundary 66 in physical space 69, such as a surgery site ina surgical operating room. A portion of working boundary 66 in turncorresponds to the planned location of the resection in the tibia 10.

The virtual boundaries and, therefore, the corresponding workingboundaries, can be any configuration or shape. Referring to FIG. 3A,virtual boundary 62 representing a proximal resection to be created inthe tibia bone 10, may be any configuration suitable for assisting auser during creation of the proximal resection in the tibia 10. Portionsof virtual boundary 62, illustrated within the virtual representation ofthe tibia bone 10, represent bone to be removed by a surgical toolSimilar virtual boundaries may be generated for holes to be drilled ormilled into the tibia bone 10 for facilitating the implantation of atibial implant on the resected tibia 10. The virtual boundaries (andtherefore, the corresponding working boundaries) may include a surfaceor surfaces that fully enclose and surround a three-dimensional volume.In an alternative embodiment, the virtual and working boundaries do notfully enclose a three-dimensional volume, but rather include both“active” surfaces and “open” portions. For example, virtual boundary 62representing a proximal resection in a tibia bone may have anessentially rectangular box-shaped “active” surface 62 a and acollapsing funnel or triangular box-shaped “active” surface 62 bconnected to the rectangular box-shaped portion, with an “open” portion64. In one embodiment, virtual boundary 62 can be created with acollapsing funnel as described in U.S. application Ser. No. 13/340,668,titled “Systems and Methods for Selectively Activating Haptic GuideZones,” filed Dec. 29, 2011, and hereby incorporated by reference hereinin its entirety. The working boundary 66 corresponding to virtualboundary 62 has the same configuration as virtual boundary 62. In otherwords, working boundary 66 guiding a proximal resection in a tibia bone10 may have an essentially rectangular box-shaped “active” surface 66 aand a collapsing funnel or triangular box-shaped “active” surface 66 bconnected to the rectangular box-shaped portion, with an “open” portion67.

In an additional embodiment, the virtual boundary 62 representing theresection in the bone 10 includes only the substantially rectangularbox-shaped portion 62 a. An end of a virtual boundary having only arectangular box-shaped portion may have an “open” top such that the opentop of the corresponding working boundary coincides with the outersurface of the bone 10. Alternatively, as shown in FIGS. 3A and 3B, therectangular box-shaped working boundary portion 66 a corresponding tovirtual boundary portion 62 a may extend past the outer surface of thebone 10.

In some embodiments, the virtual boundary 62 representing a resectionthrough a portion of the bone may have an essentially planar shape, withour without a thickness. Alternatively, virtual boundary 62 can becurved or have an irregular shape. Where the virtual boundary 62 isdepicted as a line or planar shape and the virtual boundary 62 also hasa thickness, the virtual boundary 62 may be slightly thicker than asurgical tool used to create the resection in the bone, such that thetool can be constrained within the active surfaces of working boundary66 while within the bone. Such a linear or planar virtual boundary 62may be planned such that the corresponding working boundary 66 extendspast the outer surface of the bone 10 in a funnel or other appropriateshape to assist a surgeon as the surgical tool 58 is approaching thebone 10. Haptic guidance and feedback (as described below) can beprovided to a user based on relationships between surgical tool 58 andthe active surfaces of working boundaries.

The surgical plan may also include virtual boundaries to facilitateentry into and exit from haptic control, including automatic alignmentof the surgical tool, as described in U.S. application Ser. No.13/725,348, titled “Systems and Methods for Haptic Control of a SurgicalTool,” filed Dec. 21, 2012, and hereby incorporated by reference hereinin its entirety.

The surgical plan, including the virtual boundaries, may be developedbased on information related to the patient's bone density. The densityof a patient's bone is calculated using data obtained from the CT, MRI,or other imaging of the patient's anatomy. In one embodiment, acalibration object representative of human bone and having a knowncalcium content is imaged to obtain a correspondence between imageintensity values and bone density measurements. This correspondence canthen be applied to convert intensity values of individual images of thepatient's anatomy into bone density measurements. The individual imagesof the patient's anatomy, with the corresponding map of bone densitymeasurements, are then segmented and used to create a three-dimensionalrepresentation (i.e. model) of the patient's anatomy, including thepatient's bone density information. Image analysis, such as finiteelement analysis (FEA), may then be performed on the model to evaluateits structural integrity.

The ability to evaluate the structural integrity of the patient'sanatomy improves the effectiveness of arthroplasty planning. Forexample, if certain portions of the patient's bone appear less dense(i.e. osteoporotic), the holes, resections and implant placement can beplanned to minimize the risk of fracture of the weakened portions ofbone. Furthermore, the planned structure of the bone and implantcombination after implementation of the surgical plan (e.g. thepost-operative bone and implant arrangement) can also be evaluated forstructural integrity, preoperatively, to improve surgical planning. Inthis embodiment, holes and/or cuts are planned and the bone model andimplant model are manipulated to represent the patient's bone andimplant arrangement after performance of the arthroplasty andimplantation procedures. Various other factors affecting the structuralintegrity of the post-operative bone and implant arrangement may betaken into account, such as the patient's weight and lifestyle. Thestructural integrity of the post-operative bone and implant arrangementis analyzed to determine whether the arrangement will be structurallysound and kinematically functional post-operatively. If the analysisuncovers structural weaknesses or kinematic concerns, the surgical plancan be modified to achieve a desired post-operative structural integrityand function.

Once the surgical plan has been finalized, a surgeon may perform thearthroplasty procedure with the assistance of haptic device 60 (step806). Through haptic device 60, the surgical system 100 provides hapticguidance and feedback to the surgeon to help the surgeon accuratelyimplement the surgical plan. Haptic guidance and feedback during anarthroplasty procedure allows for greater control of the surgical toolcompared to conventional arthroplasty techniques, resulting in moreaccurate alignment and placement of the implant. Furthermore, hapticguidance and feedback is intended to eliminate the need to use K-wiresand fluoroscopy for planning purposes. Instead, the surgical plan iscreated and verified using the three-dimensional representation of thepatient's anatomy, and the haptic device provides guidance during thesurgical procedure.

“Haptic” refers to a sense of touch, and the field of haptics relates tohuman interactive devices that provide tactile and/or force feedback toan operator. Tactile feedback generally includes tactile sensations suchas, for example, vibration. Force feedback (also known as “wrench”)refers to feedback in the form of force (e.g., resistance to movement)and/or torque. Wrench includes, for example, feedback in the form offorce, torque, or a combination of force and torque. Haptic feedback mayalso encompass disabling or altering the amount of power provided to thesurgical tool, which can provide tactile and/or force feedback to theuser.

Surgical system 100 provides haptic feedback to the surgeon based on arelationship between surgical tool 58 and at least one of the workingboundaries. The relationship between surgical tool 58 and a workingboundary can be any suitable relationship between surgical tool 58 and aworking boundary that can be obtained by the navigation system andutilized by the surgical system 100 to provide haptic feedback. Forexample, the relationship may be the position, orientation, pose,velocity, or acceleration of the surgical tool 58 relative to one ormore working boundaries. The relationship may further be any combinationof position, orientation, pose, velocity, and acceleration of thesurgical tool 58 relative to one or more working boundaries. The“relationship” between the surgical tool 58 and a working boundary mayalso refer to a quantity or measurement resulting from anotherrelationship between the surgical tool 58 and a working boundary. Inother words, a “relationship” can be a function of another relationship.As a specific example, the “relationship” between the surgical tool 58and a working boundary may be the magnitude of a haptic force generatedby the positional relationship between the surgical tool 58 and aworking boundary.

During operation, a surgeon manipulates the haptic device 60 to guide asurgical tool 58 coupled to the device. The surgical system 100 provideshaptic feedback to the user, through haptic device 60, to assist thesurgeon during creation of the planned holes, cuts, or othermodifications to the patient's bone needed to facilitate implantation ofthe femoral and tibial implants. For example, the surgical system 100may assist the surgeon by substantially preventing or constraining thesurgical tool 58 from crossing a working boundary. The surgical system100 may constrain the surgical tool from crossing a working boundary byany number and combination of haptic feedback mechanisms, including byproviding tactile feedback, by providing force feedback, and/or byaltering the amount of power provided to the surgical tool. “Constrain,”as used herein, is used to describe a tendency to restrict movement.Therefore, the surgical system may constrain the surgical tool 58directly by applying an opposing force to the haptic device 60, whichtends to restrict movement of the surgical tool 58. The surgical systemmay also constrain the surgical tool 58 indirectly by providing tactilefeedback to alert a user to change his or her actions, because alertinga user to change his or her actions tends to restrict movement of thesurgical tool 58. In a still further embodiment, the surgical system 100may constrain the surgical tool 58 by limiting power to the surgicaltool 58, which again tends to restrict movement of the tool.

In various embodiments, the surgical system 100 provides haptic feedbackto the user as the surgical tool 58 approaches a working boundary, uponcontact of the surgical tool 58 with the working boundary, and/or afterthe surgical tool 58 has penetrated the working boundary by apredetermined depth. The surgeon may experience the haptic feedback, forexample, as a vibration, as a wrench resisting or actively opposingfurther movement of the haptic device, or as a solid “wall”substantially preventing further movement of the haptic device. The usermay alternatively experience the haptic feedback as a tactile sensation(e.g. change in vibration) resulting from alteration of power providedto the surgical tool 58, or a tactile sensation resulting from cessationof power provided to the tool. If power to the surgical tool is alteredor stopped when the surgical tool 58 is drilling, cutting, or otherwiseoperating directly on bone, the surgeon will feel haptic feedback in theform of resistance to further movement because the tool is no longerable to drill, cut, or otherwise move through the bone. In oneembodiment, power to the surgical tool is altered (e.g. power to thetool is decreased) or stopped (e.g. the tool is disabled) upon contactbetween the surgical tool 58 and a working boundary. Alternatively, thepower provided to the surgical tool 58 may be altered (e.g. decreased)as the surgical tool 58 approaches a working boundary.

In another embodiment, the surgical system 100 may assist the surgeon increating the planned holes, cuts, and other modifications to the bone byproviding haptic feedback to guide the surgical tool 58 towards or alonga working boundary. As one example, the surgical system 100 may provideforces to the haptic device 60 based on a positional relationshipbetween the tip of surgical tool 58 and the closest coordinates of aworking boundary. These forces may cause the surgical tool 58 toapproach the closest working boundary. Once the surgical tool 58 issubstantially near to or contacting the working boundary, the surgicalsystem 100 may apply forces that tend to guide the surgical tool 58 tomove along a portion of the working boundary. In another embodiment, theforces tend to guide the surgical tool 58 to move from one portion ofthe working boundary to another portion of a working boundary (e.g. froma funnel-shaped portion of the working boundary to a rectangularbox-shaped portion of a working boundary).

In yet another embodiment, the surgical system 100 is configured toassist the surgeon in creating the planned holes, cuts, andmodifications to the bone by providing haptic feedback to guide thesurgical tool from one working boundary to another working boundary. Forexample, the surgeon may experience forces tending to draw the surgicaltool 58 towards working boundary 66 when the user guides the surgicaltool 58 towards working boundary 66. When the user subsequently removesthe surgical tool 58 from the space surrounded by working boundary 66and manipulates the haptic device 60 such that the surgical tool 58approaches a second working boundary (not shown), the surgeon mayexperience forces pushing away from working boundary 66 and towards thesecond working boundary.

Haptic feedback as described herein may operate in conjunction withmodifications to the working boundaries by the surgical system 100.Although discussed herein as modifications to “working boundaries,” itshould be understood that the surgical system 100 modifies the virtualboundaries, which correspond to the working boundaries. Some examples ofmodifications to a working boundary include: 1) reconfiguration of theworking boundary (e.g. a change in shape or size), and 2) activating anddeactivating the entire working boundary or portions of the workingboundary (e.g. converting “open” portions to “active” surfaces andconverting “active” surfaces to “open” portions). Modifications toworking boundaries, similarly to haptic feedback, may be performed bythe surgical system 100 based on a relationship between the surgicaltool 58 and one or more working boundaries. Modifications to the workingboundaries further assist a user in creating the required holes and cutsduring an arthroplasty procedure by facilitating a variety of actions,such as movement of the surgical tool 58 towards a bone and cutting ofthe bone by the surgical tool 58.

In one embodiment, modifications to the working boundary facilitatemovement of the surgical tool 58 towards a bone 10. During a surgicalprocedure, because the patient's anatomy is tracked by the navigationsystem, the surgical system 100 moves the entirety of working boundary66 in correspondence with movement of the patient's anatomy. In additionto this baseline movement, portions of working boundary 66 may bereshaped and/or reconfigured to facilitate movement of the surgical tool58 towards the bone 10. As one example, the surgical system may tiltfunnel-shaped portion 66 h of working boundary 66 relative to therectangular box-shaped portion 66 a during the surgical procedure basedon a relationship between the surgical tool 58 and the working boundary66. The working boundary 66 can therefore be dynamically modified duringthe surgical procedure such that the surgical tool 58 remains within thespace surrounded by the portion of working boundary 66 as the surgicaltool 58 approaches the bone 10.

In another embodiment, working boundaries or portions of workingboundaries are activated and deactivated. Activating and deactivatingentire working boundaries may assist a user when the surgical tool 58 isapproaching the bone 10. For example, a second working boundary (notshown) may be deactivated during the time when the surgeon isapproaching the first working boundary 66 or when the surgical tool 58is within the space surrounded by the first working boundary 66.Similarly, the first working boundary 66 may be deactivated after thesurgeon has completed creation of a first corresponding resection and isready to create a second resection. In one embodiment, working boundary66 may be deactivated after surgical tool 58 enters the area within thefunnel-portion leading to the second working boundary but is stilloutside of first funnel-portion 66 b. Activating a portion of a workingboundary converts a previously open portion (e.g. open top 67) to anactive surface of the working boundary. In contrast, deactivating aportion of the working boundary converts a previously active surface(e.g. the end portion 66 c of working boundary 66) of the workingboundary to an “open” portion.

Activating and deactivating entire working boundaries or their portionsmay be accomplished dynamically by the surgical system 100 during thesurgical procedure. In other words, the surgical system 100 may beprogrammed to determine, during the surgical procedure, the presence offactors and relationships that trigger activation and deactivation ofvirtual boundaries or portions of the virtual boundaries. In anotherembodiment, a user can interact with the surgical system 100 (e.g. byusing the input device 52) to denote the start or completion of variousstages of the arthroplasty procedure, thereby triggering workingboundaries or their portions to activate or deactivate.

In view of the operation and function of the surgical system 100 asdescribed above, the discussion will now turn to methods ofpreoperatively planning the surgery to be performed via the surgicalsystem 100, followed by a detailed discussion of methods of registeringthe preoperative plan to the patient's actual bone and also toapplicable components of the surgical system 100.

The haptic device 60 may be described as a surgeon-assisted device ortool because the device 60 is manipulated by a surgeon to perform thevarious resections, drill holes, etc. In certain embodiments, the device60 may be an autonomous robot, as opposed to surgeon-assisted. That is,a tool path, as opposed to haptic boundaries, may be defined forresecting the bones and drilling holes since an autonomous robot mayonly operate along a pre-determined tool path such that there is no needfor haptic feedback. In certain embodiments, the device 60 may be acutting device with at least one degree of freedom that operates inconjunction with the navigation system 42. For example, a cutting toolmay include a rotating burr with a tracker on the tool. The cutting toolmay be freely manipulate-able and handheld by a surgeon. In such a case,the haptic feedback may be limited to the burr ceasing to rotate uponmeeting the virtual boundary. As such, the device 60 is to be viewedbroadly as encompassing any of the devices described in thisapplication, as well as others.

II. Preoperative Planning of Arthroplasty Procedure

The preoperative planning process disclosed herein includes a boneresection depth determination and an anterior shaft notching assessment.The bone resection depth determination includes selecting andpositioning three dimensional computer models of candidate femoral andtibial implants relative to three dimensional computer models of thepatient's distal femur and proximal tibia to determine a position andorientation of the implants that will achieve a desirable surgicaloutcome for the arthroplasty procedure. As part of this assessment, thedepths of the necessary tibial and femoral resections are calculated,along with the orientations of the planes of those resections.

The anterior shaft notching assessment includes determining whether ornot an anterior flange portion of the three dimensional model of theselected femoral implant will intersect the anterior shaft of the threedimensional model of the patient's distal femur when the implant threedimensional model is positioned and oriented relative to the femur threedimensional model as proposed during the bone resection depthdetermination. Such an intersection of the two models is indicative ofnotching of the anterior femoral shaft, which must be avoided.

Each of these two preoperative planning processes is discussed below indetail and in turn.

A. Bone Resection Depth

FIGS. 4A and 4B respectively illustrate three dimensional computermodels 200, 202 of a proximal end of a generic tibia 200 and a distalend of a generic femur 202. In certain embodiments, each threedimensional model represents a statistical average of its respectivebone type according to both size and shape. For example, in oneembodiment, generic tibia model 200 is a result of an analysis of themedical images (e.g., CT, MRI, X-ray, etc.) of many (e.g., thousands ortens of thousands) of actual tibias with respect to size and shape, andthis analysis is used to generate the generic tibia model 200, which isa statistical average of the many actual tibias. Similarly, genericfemur model 202 is a result of an analysis of the medical images (e.g.,CT, MRI, X-ray, etc.) of many (e.g., thousands or tens of thousands) ofactual femurs with respect to size and shape, and this analysis is usedto generate the generic femur model 202, which is a statistical averageof the many actual femurs.

In certain embodiments, each three dimensional model represents arandomly selected bone from a catalog or library of bones. The libraryof bones may include computer models of actual bones (e.g., cadaveric)and/or computer models of medical bone models, among others. While themodels 200, 202 could be any such bone models, for the purposes of thepresent disclosure, reference will be made to the generic tibia 200 andgeneric femur 202 as representing a statistical average of a tibia andfemur, respectively, according to size and shape. As indicated in FIG.4A, target points 204, 208 are identified on the generic tibia model200. In certain embodiments, as seen in FIG. 4A, the most distallyrecessed point 204 on the tibial lateral condyle recess 206 and the mostdistally recessed point 208 on the tibial medial condyle recess 210 areidentified and electronically stored along with the generic tibia model200. Such most distally recessed tibial condyle points 204, 208 willtypically be centered medial-lateral and anterior-posterior in therespective tibial condyle recesses 206, 210. The most distally recessedtibial condyle points 204, 208 may be depicted on the generic tibiamodel 200 as circular or spherical points, as shown in FIG. 4A. Incertain embodiments, the target points 204, 208 may be located on otherportions of the tibia model 200. For example, in certain embodiments,the target points 204, 208 may be the most proximally proud or mostproximally extending point on the generic tibia model 200. Additionally,in certain embodiments, the target points 204, 208 may be the center ofthe condyles, or points located a certain fraction (e.g., ⅔) from theanterior edge, which may represent a lowpoint on a tibial insertimplanted on the generic tibia model 200. These and other points 204,208 are possible without departing from the scope of the presentdisclosure. For the purposes of the present disclosure, reference willbe made to the most distally recessed point 204 on the tibial lateralcondyle recess 206 and the most distally recessed point 208 on thetibial medial condyle recess 210.

As illustrated in FIG. 4B, the most distal point 212 and the mostposterior point 214 on the femoral lateral condyle 216 and the mostdistal point 218 and the most posterior point 220 on the femoral medialcondyle 222 are identified and electronically stored along with thegeneric femur model 202. The most distal femoral condyle points 212, 218and most posterior femoral condyle points 214, 220 may be depicted onthe generic femur model 202 as circular or spherical points, as depictedin FIG. 4B. In FIG. 4B, the distal points 212, 218 and the posteriorpoints 214, 220 are identified on the generic femur model 202 when themodel 202 is at zero degrees rotation in the sagittal plane. That is,the femur model 202 is in an un-flexed position or orientation. Thegeneric femur model 202, however, may be rotated in the sagittal planeto adjust for the planned flexion of the femoral component to beimplanted on the femur. In certain embodiments, the generic femur model202 may be rotated two degrees, among other degrees, in the sagittalplane, and the distal points 212, 218 and the posterior points 214, 220may be identified on the model 202 in this flexed orientation.

As discussed above in the overview of the surgical system, medicalimages of the patient tibia and femur are segmented and then compliedinto three dimensional meshes or computer models of the patient tibiaand femur. FIGS. 5A-5C respectively illustrate coronal, axial ortransverse, and sagittal views of the proximal end of the threedimensional computer model of the patient tibia (i.e., the patient tibiamodel 224), and FIGS. 6A-6C respectively illustrate coronal, axial ortransverse, and sagittal views of the distal end of the threedimensional computer model of the patient femur (i.e., patient femurmodel 226). While the three dimensional computer models of the patienttibia and femur are described as being generated from segmenting medicalimages (e.g., CT, MRI), it is foreseen that other methods of generatingpatient models may be employed. For example, patient bone models orportions thereof may be generated intra-operatively via registering abone or cartilage surface in one or more areas of the bone. Such aprocess may generate one or more bone surface profiles. Thus, thevarious methods described herein are intended to encompass threedimensional bone models generated from segmented medical images (e.g.,CT, MRI) as well as intra-operative imaging methods, and others.

1. Fine-Tuning Most Distally Recessed Tibial Condyle Points on PatientTibia Model

As can be understood from a comparison of FIGS. 4A and 5A-5C, the mostdistally recessed tibial condyle points 204, 208 of the generic tibialmodel 200 have been imported or mapped onto the corresponding locationsof the patient tibia model 224. An affine transformation is used to mapthe points 204, 208 from the generic tibial model 200 to the patienttibia model 224. More specifically, the target points 204, 208 from thegeneric tibial model 200 are mapped onto/into the patient tibial model224 by first transforming the target points 204, 208 using the alreadycomputed affine transform and then finding the closest surface pointfrom each transformed target point to the segmented surface of thepatient tibial model 224. As a result and as can be understood fromFIGS. 5A-5C, the most distally recessed tibial condyle points 204, 208end up being positioned at or very close to the most distally recessedlocations on the lateral and medial tibial condyles of the patient tibiamodel 224. In some embodiments and instances, the locations of thepoints 204, 208 may be scaled according to the medial-lateral scalingfactor between generic and patient models 200, 224. The transformationprocess may be similarly accomplished with alternative, previouslymentioned target points 204, 208 such as the center of the condyle, themost proximally proud lateral condyle, etc. Generally speaking, anytarget point(s) on the generic bone model may be transformed to thepatient specific bone model such that the target points 204, 208 end upbeing positioned at or very close to the desired locations on thepatient specific bone model.

It is noted that the generic model 200 and the patient tibia model 224may share a common coordinate system to aid in initial alignment. Theorigin of the patient tibia model 224 may be the top center of the tibiaas defined by a CT landmarking process. The system or user may definethese points. The generic model 200 may have a predefined originselected by the system or a user in the same manner as is done for thepatient tibia model 224.

Refinement of the distally recessed tibial condyle points 204, 208 maybe accomplished by identifying the real local minimum on the patienttibia model 224, identifying the real local maximum on the patient tibiamodel 224, identifying an edge location (e.g., anterior edge),identifying a tangential point, and finding a point where the surfacematches a certain slope, etc. Additional or alternative refinement ofthe distally recessed tibial condyle points 204, 208 may utilize similarmethods and functions described in reference to the femur.

The patient tibia model 224 and the points 204, 208 thereon may bedepicted on the display 54 as a three dimensional computer model capableof being rotated and moved. Additionally or alternatively, the patienttibia model 224 and the points 204, 208 thereon may be depicted on thedisplay 54 in three different views, namely, a coronal view, an axial ortransverse view, and a sagittal view as respectively illustrated inFIGS. 5A-5C. Where one or more of the points 204, 208 is hidden by bonestructure of the model 224, for example, as is the case in FIGS. 5A and5C, the hidden points 204, 208 may be depicted translucent or in anotherdepiction that indicates the points are present, but located behind somebone structure in the view. In certain embodiments where one or more ofthe points 204, 208 is hidden by the bone structure of the model 224,the bone model 224 may be depicted translucent, so the points 204, 208are identifiable behind the occluding bone structure. Where the one ormore of the points 204, 208 are fully visible in a view (in other words,not hidden by bone structure of the model 224), as is in the case ofFIG. 5B, the visible points 204, 208 may be depicted as solid fullyvisible points to indicate the points are not hidden by bone structureof the model 224 but are fully visible in the view.

These points 204, 208, when properly positioned on the patient tibiamodel 224, can serve as bone resection depth points to be used tocalculate the depth of bone resections to the patient tibia that willallow a selected tibial implant (in conjunction with a selected femurimplant) to achieve a desired surgical outcome when the actual implantsare implanted onto the patient's tibia and femur as part of thearthroplasty procedure preoperatively planned as described herein.

Once the target points, such as the most distally recessed tibialcondyle points 204, 208, have been properly located on the patient tibiamodel 224 as described above, these points 204, 208 can be used with athree dimensional computer model of a candidate tibial implant 300, ordata associated with such an implant 300, to preoperatively calculatethe associated bone resections that need to be made in the actualpatient bone to receive the actual tibial implant to achieve a desiredsurgical outcome from implanting the actual tibial implant onto theactual patient bone during the actual arthroplasty procedure.

FIG. 11 is a distal-anterior view of a three dimensional computer modelof the candidate tibial implant (i.e., the tibial implant model 300)illustrating its bone resection contacting surface 302 distally oppositeits tibial plateau 304. As can be understood from FIGS. 12A-12C, whichrespectively illustrate coronal, axial or transverse, and sagittal viewsof the tibial implant model 300 superimposed on the proximal end of thethree dimensional computer model of the patient tibia (i.e., the patienttibia model 224), one or both of the points 204, 208 may be aligned witha similar or equivalent most distally recessed tibial condyle point orregion on the articular surface of the tibial plateau 304 of the implantmodel 300, thereby defining a proposed tibial resection 306 that extendsalong the bone resection contacting surface 302 of the implant model300. The defined proposed tibial resection 306 is defined according toresection depth and planar orientation. Of course, the defined proposedtibial resection 306 can be adjusted or modified by preoperative, and/orin some embodiments, intraoperative, surgeon input by changing theresection depth distally or proximally relative to the points 204, 208,changing the size of the candidate tibial implant model 300 to a smalleror larger size, changing the planar orientation of the proposedresection 306 to account for a desired varus-valgus, internal-external,or extension-flexion rotation, to cause both points 204, 208 or only asingle point 204, 208 to correspond to similar points on the lateral andmedial articular surfaces of the tibial plateau 304 of the implant model300, depending on whether or not an anatomic (natural) alignment issought or a more traditional mechanical axis alignment is sought.

FIGS. 12A-12C are illustrative of a situation where just a single point204, 208 is aligned with a similar point or region on one of thearticular surfaces of the tibial plateau 304 of the implant model 300.For example, as can be seen in FIGS. 12A and 12C, the lateral point 204is aligned with a similar point or region on the lateral articularsurface of the tibial plateau 304 of the implant model 300, but themedial point 208 is not aligned with its similar point or region on themedial plateau of the implant model 300. Thus, as can be understood fromFIG. 12B, the medial point 208 is shown in dashed lines to representthat it would appear as transparent on the computer display 54 due tobeing recessed within the volume of the implant model 300, and thelateral point 208 is shown as a solid circle to represent that it wouldappear solid on the computer display due to being on the lateralarticular surface of the tibial plateau of the implant model 300. It isnoted that the tibial implant model 300 may be depicted transparently sothat the resection depth is visible through the implant model 300. Withonly the single matching of the points, which happens to be on thelateral side, the orientation of the bone resection contacting surface302 of the implant model 300, and as a result, the orientation of theproposed resection plane 306, is then determined by maintaining thematching of the lateral points while achieving a desired angle of theproposed resection plane 306 relative to an axis of the patient's leg,femur or tibia, such as, for example, the tibial mechanical axis or legmechanical axis. Once the surgeon has approved the depth and orientationof the proposed tibial resection plane 306, the associated data can beprovided to the surgical system 100 for use by the navigation system inguiding the haptic device 60 during the surgery, and the resectedpatient tibia model 224 may be represented to the surgeonintra-operatively as indicated in FIGS. 15A-15C, which are various viewsof the tibia model 224 as proposed to be resected and illustrating theproposed tibial resection 306.

While the preceding discussion of defining the proposed tibial resectionplane 306 has been made in the context of superimposing a candidatetibial implant 300 on the tibia model 224 and showing such superimposingvisually on the computer display 54 of the system 100, in otherembodiments, such a process can take place by data representative of thecandidate tibial implant 300, not requiring a three dimensionalrepresentation of the candidate tibial implant or its actual visualrepresentation on the computer display 54.

2. Fine-Tuning Most Posterior and Most Distal Femoral Condyle Points onPatient Femur Model

As can be understood from a comparison of FIGS. 4B and 6A-6C, the mostdistal femur condyle points 212, 218 and the most posterior femurcondyle points 214, 220 of the generic femoral model 202 have beenimported or mapped onto the corresponding locations of the patient femurmodel 226. As discussed with reference to the tibial transformation, anaffine transform is used to map the points 212, 214, 218, 220 from thegeneric femur model 202 to the patient femur model 226. As a result andas can be understood from FIGS. 6A-6C, the most distal femoral condylepoints 212, 218 end up being positioned at or very close to the mostdistal locations on the lateral and medial femoral condyles of thepatient femur model 226. Similarly, the most posterior femoral condylepoints 214, 220 end up being positioned at or very close to the mostposterior locations on the lateral and medial femoral condyles of thepatient femur model 226. In some embodiments and instances, thelocations of the points 212, 214, 218, 220 may be scaled according tothe medial-lateral scaling factor between generic and patient models202, 226. In some embodiments and instances, the affine transform mayincorporate the scaling functionality.

It is noted that the generic model 202 and the patient femur model 226may share a common coordinate system to aid in initial alignment. Theorigin of the patient femur model 226 for a total knee arthroplasty maybe the distal trochlear groove, as defined by a CT landmarking process.The origin of the patient femur model 226 for a partial kneearthroplasty may be the midpoint center between the medial and lateralepicondyles, as defined by a CT landmarking process. The system or usermay define these points. The generic model 202 may have a predefinedorigin selected by the system or a user in the same manner as is donefor the patient femur model 226.

In one embodiment, the “most distal” and “most posterior” points on thefemoral condyle surfaces are used in the sense of a femoral implantplaced at two degrees of flexion or at another degree of flexion asreviewed and directed by a surgeon. Also, for any of the points 204, 208of the tibia model 224 or the points 212, 214, 218, 220 of the femurmodel 226, these points should not be placed on an osteophyte or anyother surface on the models not likely to be referenced or used by asurgeon in the preoperative planning. Determining whether or not thepoints 204, 208, 212, 214, 218, 220 lie on an osteophyte will bediscussed below.

Once the points 212, 214, 218, 220 have been initially mapped onto thepatient femur model 226 from the generic femur model 202 via the affinetransform, the locations of the points 212, 214, 218, 220 on the patientfemur model 226 are adjusted to final locations via an algorithm thatfunctions as now described.

A virtual implant coordinate system is placed at two degrees of flexionfrom the femoral mechanical axis coordinate space. Theanterior-posterior and proximal-distal direction of this coordinatesystem is used in the following discussion regarding the femur resectiondepth points.

As discussed in detail in the immediately following paragraphs withrespect to FIGS. 7 and 8, for each of the two posterior points 214, 220,the algorithm conducts a search around the initial location of eachpoint 214, 220, and the final adjusted location of each point 214, 220is determined to be the most posterior vertex of all triangular surfacemesh faces intersecting a sphere centered at or near the initiallocation of each point 214, 220. In one embodiment, the radius of thesphere 230 is seven millimeters if the patient femur model 226substantially matches the generic femur model 202 with respect tomedial-lateral size. If scaling is needed due to medial-lateral sizedifferences between the patient femur model 226 and the generic femurmodel 202, then the sphere 230 may be scaled larger or smaller thanseven millimeters in radius depending on the scaling between the twomodels 202, 226.

Thus, as can be understood from FIGS. 7 and 8, which are, respectively,an enlarged view of a triangular surface mesh 228 of a posteriorcondylar region of a three dimensional patient femur computer model 226and a flow chart outlining the method of adjusting the placement of themapped posterior points 214, 220 on the patient femur model 226, theposterior points 214, 220 are mapped from the generic femur model 202 tothe condyles of the patient femur model 226 [block 250]. Themedial-lateral and anterior-posterior scaling factors are determinedbetween the generic femur model 202 and the patient femur model 226, andthese scaling factors are stored for later use [block 252]. For eachposterior point 214, 220 on the patient femur model, a virtual sphere230 is centered at the point 214, 220, the sphere 230 having a radius Rthat is 7 mm multiplied by the medial-lateral scaling factor [block254].

As illustrated in FIG. 7, the initial location of a posterior point 214mapped from the generic femur model 202 onto the patient femur model 226is indicated at the location called out by Arrow A. As seen in FIG. 7,the posterior point 214 is located on the surface mesh 228 as computedby the affine transform. In the case of other transforms, the point 214may, however, be spaced outwardly apart from the triangular surface mesh228 or be recessed within the triangular surface mesh 228. The initiallocation at Arrow A of the posterior point 214 is surrounded by thesphere 230, which, as discussed above, may have a radius of sevenmillimeters or other radii depending on M-L scaling between the twomodels 202, 226. The sphere 230 intersects a number of triangular faces232 and vertices of the surface mesh 228, and the algorithm adjusts(i.e., moves) the posterior point 214 as indicated by the dashed arrowto the vertex that is most posterior of any of the vertexes of any ofthe triangular faces 232 intersected by the sphere 230 [block 256]. Theresulting adjusted final location of the posterior point 214 on thepatient femur model 226 is indicated by Arrow B in FIG. 7. The posteriorresection depth is then determined based on the adjusted final locationof the posterior point 214 [block 258]. The surgical system 100 may thengenerate resection data using the posterior resection depth. Theresection data may be used during the intraoperative part of thearthroplasty procedure and be employed as a haptic boundary forcontrolling the haptic device 60 or surgical robot. Additionally oralternatively, the resection data may be utilized by a surgical robotduring the arthroplasty procedure. Additionally or alternatively, theresection data may be utilized by a navigation system during thearthroplasty procedure. The navigation system may operate in conjunctionwith an autonomous robot or a surgeon-assisted device in performing thearthroplasty procedure. An autonomous robot, such as a cutting devicewith at least two degrees of freedom (e.g., rotating burr andtranslation capabilities) may perform the arthroplasty procedure withthe resection data utilized as a tool path for performing a resection. Asurgeon-assisted device, such as the haptic device 60 described hereinor a cutting tool with at least one degree of freedom (e.g., rotatingburr moved or translated by a surgeon), may perform the arthroplastyprocedure with the resection data being a virtual or haptic boundary forcontrolling or limiting certain movements of the cutting tool (e.g.,depth of resection). Thus, the steps in FIG. 8 may describe a method ofgenerating resection plane data for use in planning an arthroplastyprocedure on a patient bone.

While a sphere 230 is described in the present disclosure, it isforeseen that other three-dimensional shapes may be employed instead ofa sphere. For example, an ellipsoid, prism, or box, among otherthree-dimensional shapes may be used without limitation and withoutdeparting from the scope of the present disclosure. Additionally oralternatively, a two-dimensional shape such as a plane or a surfacewithout a thickness may be used herein.

While the technique for identifying the location of the most posteriorpoint 214 on the patient femur model 226 is not iterative, in certainembodiments, finding the location may be an iterative process. Incertain instances, the bone surface at the posterior end may berelatively healthy and non-diseased. Thus, determining the location ofthe most posterior point 214 may be accomplished with a non-iterativeapproach.

As discussed in detail in the immediately following paragraphs withrespect to FIGS. 8-10C, each of the two distal points 212, 218, thealgorithm conducts a search around the initial location of each point212, 218, and the final adjusted location of each point 212, 218 isdetermined to be the most distal of all surface mesh vertices locatedinside an ellipsoid 240 centered at or near the initial location of eachpoint 212, 218 where X is in the medial-lateral direction, Y is in theanterior-posterior direction, and Z is in the proximal-distal direction.As the algorithm progresses through its iterations, the size of theellipsoid 240 is dynamically adjusted, depending on whether: (1) thefound most distal point is close to the boundary of the ellipsoid 240;and (2) the proximal-distal span of a region around the found point islarge, indicating that the point is close to the medial-lateral edge ofthe condyle or close to osteophytes. A new most distal point is foundafter each ellipsoid iteration adjustment until the process is satisfiedby finding the final most distal point 212, 218.

It is noted that while the present disclosure describes an ellipsoid240, it is foreseen that other three-dimensional shapes may be employedinstead of an ellipsoid. For example, a sphere, prism, or box, amongother three-dimensional shapes may be used without limitation andwithout departing from the scope of the present disclosure. Additionallyor alternatively, a two-dimensional shape such as a plane or a surfacewithout a thickness may be used herein.

With respect to the operation of the algorithm as detailed below andmentioned immediately above, if the distal point is too close to theellipsoid boundary, then this means that a more distal point existsoutside the ellipsoid and the search ellipsoid is enlarged. As willbecome evident from the following discussion, this process isessentially repeated with some variation in size and shape of the searchvolume (i.e., the ellipsoid and later used spheres as discussed below)and checks on the process until the most distal point lies within thesearch volume and not on its edge. Also, as will become evident from thefollowing discussion, one of the checks on the process is where thesemi-minor axis R_(Z) of the current iteration of the process has anexcessive jump from the most distal point from the semi-minor axis R_(Z)of the immediately preceding iteration of the process. If so, it isassumed the search volume has encompassed an osteophyte. In response tothis osteophyte, the search volume is then reduced in size by the amountof the excessive jump and the most distal point is then found.

In one embodiment, the semi-minor axes (Rx and Rz) of the ellipsoid areequal and are each seven millimeters if the patient femur model 226substantially matches the generic femur model 202 with respect tomedial-lateral size. If scaling is needed due to medial-lateral sizedifferences between the patient femur model 226 and the generic femurmodel 202, then the semi-minor axes of the ellipsoid may be scaledlarger or smaller than seven millimeters depending on the M-L scalingbetween the two models 202, 226. Similarly, the semi-major axis (Ry) ofthe ellipsoid is ten millimeters if the patient femur model 226substantially matches the generic femur model 202 with respect toanterior-posterior size. If scaling is needed due to anterior-posteriorsize differences between the patient femur model 226 and the genericfemur model 202, then the semi-major axis of the ellipsoid may scaledlarger or smaller than ten millimeters depending on the A-P scalingbetween the two models 202, 226.

Thus, as can be understood from FIG. 8 and continued with FIGS. 9A and10, which are, respectively, an enlarged view of a triangular surfacemesh 228 of a distal condylar region of a three dimensional patientfemur computer model 226, and a flow chart outlining the method ofadjusting the placement of the mapped distal points 212, 218 on thepatient femur model 226, the distal points 212, 218 are mapped from thegeneric femur model 202 to the condyles of the patient femur model 226[block 250]. The medial-lateral and anterior-posterior scaling factorsare determined between the generic femur model 202 and the patient femurmodel 226, and these scaling factors are stored for later use [block252]. As shown in FIG. 9A and outlined in FIG. 10A, for each distalpoint 212, 218 on the patient femur model, a virtual ellipsoid 240 iscentered at the point 212, 218, the ellipsoid 240 having semi-minor axesof R_(X) and R_(Z) and a semi-major axis R_(Y), wherein R_(X) and R_(Z)each respectively equal 7 mm multiplied by the anterior-posteriorscaling factor, and R_(Y) equals 10 mm multiplied by theanterior-posterior scaling factor [block 260]. These axes R_(X), R_(Z)and R_(Y) are illustrated in FIG. 9B, which is an enlarged isometricview of the ellipsoid 240 employed in FIG. 9A.

As illustrated in FIG. 9A, the initial location of a distal point 212mapped from the generic femur model 202 onto the patient femur model 226is indicated at the location called out by Arrow A, which is on thetriangular surface mesh 228. As indicated previously, a differenttransform may position the initial distal point 212 spaced outwardlyapart from the triangular surface mesh 228 or recessed within thetriangular surface mesh 228, depending on the particular transformemployed. The initial location at Arrow A of the distal point 212 on thesurface mesh 228 is surrounded by the ellipsoid 240, which, as discussedabove, may have semi-minor axes R_(X), R_(Z) that are each sevenmillimeters or other lengths depending on A-P scaling between the twomodels 202, 226, and a semi-major axis R_(Y) this is ten millimeters orother lengths depending on A-P scaling between the two models 202, 226.The ellipsoid 240 encompasses a number of vertices 242 of the triangularfaces 232 of the surface mesh 228, and the algorithm finds the mostdistal vertex of all the vertices 242 inside the ellipsoid 240, which isthe vertex 242 identified in FIG. 9A by Arrow B [block 262]. Thealgorithm then assesses whether or not the most distal vertex 214identified in FIG. 9A by Arrow B is too close to the boundary of theellipsoid 240 [block 264].

In one embodiment, the algorithm defines an identified most distalvertex 242 (indicated by arrow B in FIG. 9A) as being too close to theboundary of the ellipsoid 240 if the functional result for theidentified most distal vertex 242 is greater than 0.65 (non-dimensional)when the position of the identified most distal vertex 242 is applied tothe ellipsoid function: f=x²/a²+y²/b²+z²/c². In the ellipsoid function,x is Tx-Px, where Tx is the x-coordinate of the target point (A in FIG.9C), and Px is the x-coordinate of the computed new distal point (B inFIG. 9C). That is, x is the distance, in the x-direction, from thecenter of the ellipse to the computed new distal point P. Similarly isthe case for y and z in the ellipsoid function. That is, y is Ty-Py,where Ty is the y-coordinate of the target point, and Py is they-coordinate of the computed new distal point. And, z is Tz-Pz, where Tzis the z-coordinate of the target point, and Pz is the z-coordinate ofthe computed new distal point. In the ellipsoid function: a is theradius, Rx=7 mm (total ML width of ellipse is 14 mm); b is the radius,Ry=10 mm (total AP length of ellipse is 20 mm); and, c is the radius,Rz=7 mm (total height of ellipse is 14 mm).

A value of 0.65 is equivalent to about 1.5 mm from the edge of theellipse. Ultimately, if the identified most distal vertex 242 is not tooclose to the boundary of the ellipsoid 240 (e.g., 1.5 mm from edge),then, as indicated by the dashed arrow in FIG. 9A, the distal point 212is moved to the identified most distal vertex 242 indicated in FIG. 9Aby arrow B as being the most distal vertex [block 266], the resultingadjusted final location of the distal point 212 on the patient femurmodel 226 being as indicated by Arrow B in FIG. 9A. This adjusted finallocation of the distal point 212 can then be used to calculate thedistal resection depth [block 267]. The distal resection depth may beused to generate resection data, which may be employed by the surgicalsystem 100 as a haptic boundary for controlling the haptic device 60 orsurgical robot. Additionally or alternatively, the resection data may beutilized by a surgical robot during the arthroplasty procedure.Additionally or alternatively, the resection data may be utilized by anavigation system during the arthroplasty procedure. The navigationsystem may operate in conjunction with an autonomous robot or asurgeon-assisted device in performing the arthroplasty procedure. Anautonomous robot, such as a cutting device with at least two degrees offreedom (e.g., rotating burr and translation capabilities) may performthe arthroplasty procedure with the resection data utilized as a toolpath for performing a resection. A surgeon-assisted device, such as thehaptic device 60 described herein or a cutting tool with at least onedegree of freedom (e.g., rotating burr moved or translated by asurgeon), may perform the arthroplasty procedure with the resection databeing a virtual or haptic boundary for controlling or limiting certainmovements of the cutting tool (e.g., depth of resection). Thus, themethods described herein for determining the location of the most distalpoint may describe a method of generating resection plane data for usein planning an arthroplasty procedure on a patient bone.

If on the other hand, as can be understood from FIGS. 10A, 10B and 9C,which is the same ellipsoid 240 of FIGS. 9A and 9B, the identified mostdistal vertex 242 (indicated by arrow B in FIGS. 9A and 9C) is too closeto the boundary of the ellipsoid 240, then, as indicated in FIG. 9C, asphere center point 250 is identified that is one millimeter towards theellipsoid center (i.e., the initial most distal point 212 indicated byarrow A in FIGS. 9A and 9C) from the identified most distal vertex 242indicated by arrow B [block 268]. As illustrated in FIG. 9C, the sphere252 is centered at the sphere center point 250 and has a radius of 2millimeters [block 270]. A superior-inferior or SI span is found for alltriangle faces 232 of the triangular surface mesh 228 that intersect theboundary of the sphere 252, wherein the SI span is: Zspan=(Zmax−Zmin)[block 272]. It is noted that the Zspan is the span height in the Zdirection (proximal-distal) from highest point to lowest point.

Describing the SI Span another way, for all triangle faces 232 containedinside the sphere 252, the vertex 242 with the smallest Z value (i.e.,lowest height) is subtracted from the vertex 242 with the largest Zvalue (i.e., highest height). Thus, the SI span measures the differencebetween the maximum point of intersection of the triangular faces 232with the sphere 252 and the minimum point of intersection of thetriangular faces 232 with the sphere 252, along one coordinate direction(e.g., z). From this, it can be determined that a change or differencebetween the minimum and maximum along a particular coordinate directioncan predict the presence of an osteophyte, which protrudes, oftenabruptly, from a boney surface.

A check is made to see if the Zspan is greater than 1.5 millimeters orthe semi-major axis R_(Y) of the current iteration of the ellipsoid 240is greater than 15 times the A-P scaling factor [block 274]. If eitherof the conditions of [block 274] are satisfied and each of thesemi-minor axes R_(X), R_(Z) of the current iteration of the ellipsoid240 are each not greater than three millimeters, then the distal point212 is moved to the identified sphere center point 250 and this finaladjusted location of the distal point 212 is used to calculate thedistal resection depth [block 276]. In this way, the Zspan is used toidentify a peak (e.g., osteophyte) in the Z direction. And if the systemdetects a peak (i.e., Zspan>1.5 mm), then the system will adjust thesearch in an attempt to find the highest elevation outside the peak.

Alternatively, if either of the conditions of [block 274] are satisfied,but the semi-minor axes R_(X), R_(Z) of the current iteration of theellipsoid 240 are each greater than three millimeters, then a newellipsoid is created to have: a semi-minor axis R_(X(NEW)) that is onemillimeter less than the semi-minor axis R_(X) of the immediatelypreceding ellipsoid in the iteration (i.e., R_(X(NEW))=R_(X)−1 mm); asemi-minor axis R_(Z(NEW)) that is one millimeter less than thesemi-minor axis R_(Z) of the immediately preceding ellipsoid in theiteration (i.e., R_(Z(NEW))=R_(Z)−1 mm); and a semi-major axisR_(Y(NEW)) that is one millimeter less than the semi-major axis R_(Y) ofthe immediately preceding ellipsoid in the iteration (i.e.,R_(Y(NEW))=R_(Y)−1 mm), and the process returns to [block 262] of FIG.10A to perform another iteration with the new ellipsoid [block 278].

Finally, if neither of the conditions of [block 274] are not satisfied,then the radius of the sphere 252 is increased to 4 millimeters and a SIspan is found for all triangles faces 232 of the triangular surface mesh228 that intersect the boundary of the sphere 252, wherein the SI spanis: Zspan=(Zmax−Zmin), and the process continues at [block 282] in FIG.10C [block 280]. A check is made to see if the Zspan associated with thenew 4 mm radius sphere 252 is greater than 2 millimeters [block 282]. Ifthe condition of [block 282] is satisfied, then the distal point 212 ismoved to the identified sphere center point 250 and this final adjustedlocation of the distal point 212 is used to calculate the distalresection depth [block 284].

While a sphere 252 is described in the present disclosure, it isforeseen that other three-dimensional shapes may be employed instead ofa sphere. For example, an ellipsoid, prism, or box, among otherthree-dimensional shapes may be used without limitation and withoutdeparting from the scope of the present disclosure. Additionally oralternatively, a two-dimensional shape such as a plane or a surfacewithout a thickness may be used herein.

If the condition of [block 282] is not satisfied, then a check is madeto see if the values for the current semi-minor axes R_(X), R_(Z) havebeen previously visited in earlier iterations [block 286]. If the valuesfor the current semi-minor axes R_(X), R_(Z) were previously visited,then the distal point 212 is moved to the identified sphere center point250 and this final adjusted location of the distal point 212 is used tocalculate the distal resection depth [block 288].

If on the other hand, the values for the current semi-minor axes R_(X),R_(Z) were not previously visited, then a new ellipsoid is created tohave: a semi-minor axis R_(X(NEW)) that is two millimeters greater thanthe semi-minor axis R_(X) of the immediately preceding ellipsoid in theiteration (i.e., R_(X(NEW))=R_(X)+2 mm); a semi-minor axis R_(Z(NEW))that is two millimeters greater than the semi-minor axis R_(Z) of theimmediately preceding ellipsoid in the iteration (i.e., R_(Z(NEW))=R_(Z)2 mm); and a semi-major axis R_(Y(NEW)) that is two millimeters greaterthan the semi-major axis R_(Y) of the immediately preceding ellipsoid inthe iteration (i.e., R_(Y(NEW))=R_(Y)+2 mm), and the process returns to[block 262] of FIG. 10A to perform another iteration with the newellipsoid [block 290].

The process previously described may be useful in detecting whether anosteophyte or other irregular boney feature is encountered whendetermining the identified most distal vertex 242 (indicated by arrow Bin FIG. 9A). Because an osteophyte may protrude from the surface of thepatient femur model 226, the most distal vertex 242 may lie on theosteophyte. But, for the purposes of mapping a distal point 212 from thegeneric femur model 202 onto the patient femur model 226, it may bebeneficial to disregard the presence of the osteophyte on the patientfemur model 226 because the osteophyte surface may be irrelevant indetermining a resection depth. That is, since resection depth is afunction of the most distal vertex 242, the most distal vertex 242should not be altered by the presence of an irregular boney feature.Thus, the process described previously may be summarized as follows.

The initial location of a distal point 212 is mapped from the genericfemur model 202 onto the patient femur model 226, which is indicated atthe location called out by Arrow A in FIG. 9A. An ellipsoid 240 iscreated based on the parameters previously described. A most distalvertex 242 is identified within the ellipsoid 240 based on theparameters previously described. If the most distal vertex 242 is nottoo close to the edge of the boundary of the ellipsoid 240, then themost distal vertex 242 is used to calculate distal resection depth, asdiscussed with reference to [Block 267]. If the most distal vertex 242is too close to the edge of the boundary of the ellipsoid 240, it mustbe determined if the most distal vertex 242 lies on an osteophyte via,in certain embodiments, the Zspan calculation described previously. Ifthe most distal vertex 242 lies on an osteophyte, the size of theellipsoid is reduced and the process continues as previously described.Finally, if the most distal vertex 242 does not lie on an osteophyte,the size of the ellipsoid is increased and the process continues aspreviously described. The process of increasing or decreasing the sizeof the ellipse can occur multiple times. For example, if the most distalpoint is near the edge of the ellipse and it is determined to not belocated on an osteophyte, then the ellipse could continue to increase insize until it either encounters an osteophyte or is determined to benear the edge.

The patient femur model 226 and the points 212, 214, 218, 220 thereonmay be depicted on the display 54 as a three dimensional computer modelcapable of being rotated and moved. Additionally or alternatively, thepatient femur model 226 and the points 212, 214, 218, 220 thereon may bedepicted on the display 54 in three different views, namely, a coronalview, an axial or transverse view, and a sagittal view as respectivelyillustrated in FIGS. 6A-6C. Where one or more of the points 212, 214,218, 220 is hidden by bone structure of the model 226, for example, asis the case with points 214, 220 in FIG. 6A and point 218 in FIG. 6C,the hidden points may be depicted translucent or in another depictionthat indicates the points are present, but located behind some bonestructure in the view. In certain embodiments, the patient femur model226 may be depicted transparently so that the points 212, 214, 218, 220are visible even if occluded by the surfaces of the patient femur model226. Where the one or more of the points 212, 214, 218, 220 are fullyvisible in a view (in other words, not hidden by bone structure of themodel 226), as is in the case with points 212, 218 in FIG. 6A, points212, 214, 218, 220 in FIG. 6B and points 212, 214, 220 in FIG. 6C, thevisible points 204, 208 may be depicted as solid fully visible points toindicate the points are not hidden by bone structure of the model 226but are fully visible in the view.

These points 212, 214, 218, 220, when properly positioned on the femurmodel 226, can serve as bone resection depth points to be used tocalculate the depth of bone resections to the patient femur that willallow a selected femur implant (in conjunction with a selected tibialimplant) to achieve a desired surgical outcome when the actual implantsare implanted onto the patient's tibia and femur as part of thearthroplasty procedure preoperatively planned as described herein.

Once the most posterior points 214, 220 and the most distal points 212,218 have been properly located on the patient femur model 226 asdescribed above, these points 212, 214, 218, 220 can be used with athree dimensional computer model of a candidate femur implant 320, ordata associated with such an implant 320, to preoperatively calculatethe associated bone resections that need to be made in the actualpatient bone to receive the actual femur implant to achieve a desiredsurgical outcome from implanting the actual femur implant onto theactual patient bone during the actual arthroplasty procedure.

FIG. 13 is a sagittal view of a three dimensional computer model of thecandidate femur implant (i.e., the femur implant model 320) illustratingits distal bone resection contacting surface 322 along with the adjacentanterior chamfer resection contacting surface 324, posterior chamferresection contacting surface 326, anterior resection contacting surface328, and posterior resection contacting surface 330, these resectioncontacting surfaces being proximal the medial and lateral condylarsurfaces of the 332 of the femur implant model 320.

As can be understood from FIGS. 14A-14C, which respectively illustratecoronal, axial or transverse, and sagittal views of the femur implantmodel 320 superimposed on the distal end of the three dimensionalcomputer model of the patient femur (i.e., the patient femur model 226),one, two, three or four of the points 212, 214, 218, 220 may be alignedwith a similar or equivalent most proximal and most distal femur condylepoints or regions on the articular surface 332 of the femur implantmodel 320, thereby defining a proposed distal femur resection 334 thatextends along the distal bone resection contacting surface 322 of theimplant model 300. In some embodiments, the defined proposed resectionmay also include proposed bone resections corresponding to the variousother bone resection contacting surfaces 324, 326, 328, 330 of thecandidate femur implant model 320, as can be understood from acomparison of FIGS. 13 and 14C.

The defined proposed distal femur resection 334 is defined according toresection depth and planar orientation. Of course, the defined proposeddistal femur resection 334 can be adjusted or modified by preoperative,and/or in some embodiments, intraoperative, surgeon input by changingthe resection depth distally or proximally relative to the points 212,214, 218, 220, changing the size of the candidate femur implant model320 to a smaller or larger size, changing the planar orientation of theproposed distal resection 334 to account for a desired varus-valgus,internal-external, or extension-flexion rotation, to cause all fourpoints 212, 214, 218, 220 or only a single pair of points to correspondto similar points on the lateral and medial articular surfaces 332 ofthe femur implant model 320, depending on whether or not an anatomic(natural) alignment is sought or a more traditional mechanical axisalignment is sought.

FIGS. 14A-14C are illustrative of a situation where just a pair ofpoints 212, 214 is aligned with a similar pair of points or regions onone of the articular surfaces 332 of the femur implant model 320. Forexample, as can be seen in FIGS. 12A-12C, the lateral points 212, 214are aligned with similar points or regions on the articular surface 334of the femur implant model 320, but the medial points 218, 220 are notaligned with their similar medial points or regions on the articularsurface 332 of the implant model 320. With only the these pairs ofpoints matching, which happens to be on the lateral side, theorientation of the distal bone resection contacting surface 322 of theimplant model 320, and as a result, the orientation of the proposedresection plane 334, is then determined by maintaining the matching ofthe lateral points while achieving a desired angle of the proposeddistal resection plane 334 relative to an axis of the patient's leg,femur or tibia, such as, for example, the femoral mechanical axis or legmechanical axis. Once the surgeon has approved the depth and orientationof the proposed femur resection plane 334, the associated data can beprovided to the surgical system 100 for use by the navigation system inguiding the haptic device 60 during the surgery, and the resectedpatient femur model 226 may be represented to the surgeonintra-operatively as indicated in FIGS. 16A-16C, which are various viewsof the femur model 226 as proposed to be resected and illustrating theproposed femur resections, including the distal resection 334.

While the preceding discussion of defining the proposed femur resectionplane 334 has been made in the context of superimposing a candidatefemur implant 320 on the femur model 226 and showing such superimposingvisually on the computer display 54 of the system 100, in otherembodiments, such a process can take place by data representative of thecandidate femur implant 320, not requiring a three dimensionalrepresentation of the candidate femur implant or its actual visualrepresentation on the computer display 54.

3. Adjusting Proposed Resection Depths for Joint Gap

To account for proper joint gap spacing between the preoperativelyplanned implant models 224, 226 that will result in a desired surgicaloutcome when the actual implants are implanted during the arthroplastyon the patient, the bone resections being made via the surgical system100 according to the preoperative planning outlined above in SubsectionsI(A)(1) and I(A)(2) of this Detailed Description, two gap distances arecalculated as part of the preoperative planning of the resection depths.The two calculated gap distances are the minimum signed distancebetween: the medial condyle surface 332 of the femur implant model 320and the medial articular surface 304 of the tibial implant model 300;and the lateral condyle surface 332 of the femur implant model 320 andthe lateral articular surface 304 of the tibial implant model 300. FIG.17 is an isometric view of the femoral articular surface 332 of thefemur implant model 320 and the tibial articular surface 304 of thetibial implant model 300. While the disclosure focuses on the bonesforming the knee joint, the teachings herein are equally application tobones forming other joints as well such as, for example, an ankle,elbow, or wrist.

The minimum gap distance is defined as positive for all points on thefemoral condyle implant that are located inside a positive Voronoiregion defined by the faces, internal edges, and internal vertices ofthe articular surface 304 of the tibial implant model 300. The minimumgap distance is defined as negative for all points on the articularsurface 332 of the femoral implant model 320 that are located inside anegative Voronoi region. Only the distance between the articularsurfaces of the models need to be considered, as these are the surfaceson which the implants contact each other.

To achieve an acceptable level of accuracy, the gap distance is computedbetween the vertices of the triangular faces of the triangular surfacemesh of the articular surface model 332 of the femur implant model 320and the triangle faces of the triangular surface mesh of the articularsurface model 304 of the tibial implant model 300, as shown in FIG. 17.Due to the fine resolution of the femoral articular surface model 320,the vertex to surface gap distance is a close approximation to the truesurface to surface gap distance.

The system 100 may employ two different algorithms for calculating thejoint gap, the first being a global search closest distance algorithm(“GSCDA”), and the second being an incremental search closest distancealgorithm (“ISCDA”). The GSCDA is guaranteed to find the minimum signeddistance between arbitrary surfaces. The ISCDA is a quick incrementallocal search algorithm that works for convex surfaces.

In the application, the gap distance for a first joint pose iscalculated with the GSCDA. It returns the gap distance and the index ofthe vertex of the surface mesh of the articular surface model 332 of thefemur implant model 320 that has the closest gap distance.

In the application, the gap distance for a second joint pose iscalculated with the ISCDA. In doing so, it references the vertexreturned from the first joint pose calculation. All the gap distancecalculations of the remaining joint poses that follow occur in the sameway; i.e., each uses the ISCDA and references the vertex from theprevious joint pose calculation.

Using the GSCDA algorithm for a single pose and then the ISCDA for theremaining poses speeds up the gap calculation. Utilizing GSCDA for eachpose would require additional time and computing resources, especiallywith many poses to analyze.

In certain instances, a tibial surface profile may be utilized that isdifferent than the anatomical or true tibial articular surface. If, forexample, the tibial articular surface is nearly as conforming as thefemoral articular surface, a modified tibial articular surface that isflattened somewhat may be used in the joint gap calculation. In certaininstances where the tibial surface profile is very conforming to thefemoral articular surface, then slight anterior-posterior and/ormedial-lateral translation may result in a virtual interferencecondition, which makes the computed signed distance show “tight” ornegative. Thus, pose positions may indicate an interference position ifthe tibia is slightly translated anterior-posterior and/ormedial-lateral, where there is actually no interference condition. Sucha measurement of perceived interference may indicate to the surgeon thatthe femoral and tibial components of an implant system should bepositioned further away from each other to eliminate the perceivedinterference condition. In order to counter the perceived interference,the signed distance may be computed between the femoral articularsurface and a generalized tibial surface that is somewhat flat orslightly concave (i.e., more flat than the true tibia).

i. Global Search Closest Distance Algorithm (“GSCDA”)

The GSCDA can be divided into a broad-phase search stage of FIG. 18 anda narrow-phase search stage of FIG. 19. A hierarchical sphere tree iscreated for each articular surface model. The tree is constructed in abottom up fashion, so each leaf node sphere encloses a single triangleface and each parent node sphere encloses its child node spheres. Duringthe broad-phase search stage of FIG. 18, the GSCDA traverses both spheretrees in a breadth-first manner while maintaining a queue of candidatenode pairs for the narrow-phase search stage, which may be similar tothe algorithm described in A Framework for Efficient Minimum DistanceComputations by David E. Johnson and Elaine Cohen, Department ofComputer Science, University of Utah (1998), which is herebyincorporated by reference herein in its entirety. Each node pairproduces lower and upper bound estimates for the gap distance betweenthe models 304, 332. A global upper bound estimate is maintained toprune candidate node pairs. If a new non-leaf node pair yields a lowerbound estimate that is greater than the global upper bound estimate, thepair is discarded during the search. Leaf node pairs are inserted into aleaf node pair list. If a node pair is not discarded, its upper boundestimate is used to update the global upper bound estimate. Thebroad-phase search is terminated when there are no more node pairs inthe queue.

As reflected in FIG. 19, the narrow-phase search stage traverses thelist of leaf node pairs and computes the gap distance between thevertices referenced in the femoral condyle component leaf nodes and thetriangle faces referenced in the tibial component leaf nodes. Thevertex-triangle pair with the smallest gap distance is selected as thesolution. The gap distance, the triangle index, as well as the closestpoint pair is returned by the algorithm.

The narrow-phase search uses the point-triangle distance calculationmethod described in Section 5.1 of Real-Time Collision Detection byChrister Ericson (2005), which is hereby incorporated by referenceherein in its entirety. To account for negative gap distances, thealgorithm is modified such that when the closest point is on a triangleface and not on a triangle edge or vertex, the sign of the distance isdetermined from the sign of the inner product of the triangle normal andthe difference vector between the point and the closest point on thetriangle.

This modified algorithm does not handle the case when the point islocated in the negative Voronoi cells of the internal edges and verticesof the tibial component model because it returns a positive distancewhen the closest point is located on any edge or vertex of the model.Due to the high resolution of the femoral condyle component model, themodified algorithm yields a reasonable approximation to the distancebetween the models, because when the closest point is located on aninternal edge or vertex of the tibial component model, there will be anearby vertex of the femoral condyle model for which the closest pointis located on a triangle face of the tibial component model. Closelyapproximating the gap distance by computing the distance between thevertices of the femoral condyle articular surfaces to the triangle facesof the tibial articular surface yields is performed quicker thancalculating from vertices of the femoral condyle articular surface tovertices of the tibial articular surface. A vertices-to-verticescalculation may yield marginal improvements in accuracy, but willrequire more computing time and, thus, be slower.

ii. Incremental Search Closest Distance Algorithm (“ISCDA”)

The ISCDA starts with a known vertex of the triangular faces of thetriangular surface mesh of the articular surface model 332 of the femurimplant model 320 and finds the locally closest vertex by searching allneighbor vertices of the current vertex. The search terminates when alladjacent vertices (first and second level) of the current vertex arefurther away from the triangle faces of the triangular surface mesh ofthe articular surface model 304 of the tibial implant model 300 than thecurrent vertex. The gap distance is computed by traversing the spheretree data structure of the tibial implant model in a depth-first mannerusing the position of the vertex as the input position.

Once the joint gap distance is determined according to the properapplication of the above-discussed GSCDA and ISCDA, the joint gap valuescan be applied to adjust, if necessary, the proposed femur and tibiaresection planes with respect to resection depth.

iii. Pose Capture and Intra-Operative Joint Gap Calculation

Once the patient femur 11 and tibia 10 are tracked by the tracking andnavigation system, the surgeon may intra-operatively capture or recordthe pose (i.e., position and orientation) of the tibia 10 relative tothe femur 10 with the surgical system 100. More particularly, thesurgeon may position the patient's femur 11 and tibia 10 in a set ofposes with different flexion angle values and capture or otherwiserecord the measured position and orientation of the tibia 10 relative tothe femur 11 for each pose. As discussed previously, thethree-dimensional femur model with the femur implant model and thethree-dimensional tibia model with the tibial implant model may bedepicted on the display screen, and the location and orientation of themodels may correspond with the physical location and orientation of thetibia 10 and femur 11.

The surgeon may then run the joint gap calculation using the GSCDA forone of the poses. The calculation may be ran on the extension pose(i.e., flexion angle about zero degrees), or a flexion pose (i.e.,flexion angle greater than zero degrees). Then, the ISCDA calculationmay be executed for the rest of the poses. In certain embodiments, thesurgeon may run the joint calculation using the GSCDA for all of theposes.

As an example, a surgeon may capture five poses corresponding to 0degrees flexion, 30 degrees flexion, 60 degrees flexion, 90 degreesflexion, and 120 degrees flexion. The GSCDA calculation is executed forone of the poses, such as the 60 degree flexion pose. Next, the ISCDAcalculation may be executed on the next-closest pose. In this example,the calculations of ISCDA may be performed in the following order: 90degrees, 120 degrees, then 30 degrees, and 0 degrees. At the beginningof each ISCDA sequence, the vertex index from the GSCDA calculation isused for initialization of the search (i.e., at 90 degrees and 30degrees). In the subsequent steps, the vertex index from the ISCDAcalculation is used from the previous step (i.e., at 120 degrees thevertex index from 90 degrees, and at 0 degrees the vertex index from 30degrees).

As another example, a method of generating resection data for use inplanning an arthroplasty procedure on a knee joint may include thefollowing steps. A computer may receive a three-dimensional femur modeland a three-dimensional femur implant model oriented relative to eachother in a first pre-planned orientation in a common three-dimensionalcoordinate system. The three-dimensional femur model may correspond tothe femur of the patient. The three-dimensional femur implant model mayinclude a medial condyle surface and a lateral condyle surface. Thecomputer may also receive a three-dimensional tibia model and athree-dimensional tibia implant model oriented relative to each other ina second pre-planned orientation in the common three-dimensionalcoordinate system. The three-dimensional tibia model may correspond tothe tibia of the patient. The three-dimensional tibia implant model mayinclude a medial articular surface and a lateral articular surface. Thethree-dimensional femur model and the three-dimensional tibia model maybe oriented relative to each other according to a pose of the femur andtibia of the patient via a navigation system. The computer may alsoreceive first position and orientation data corresponding to a firstposition and orientation of the femur and the tibia in a first pose. Thecomputer may also calculate a first signed distance between the medialcondyle surface of the three-dimensional femur implant model and a firstpoint on or associated with the three-dimensional tibia implant model inthe first pose. The computer may also calculate a second signed distancebetween the lateral condyle surface of the three-dimensional femurimplant model and a second point on or associated with thethree-dimensional tibia implant model in the first pose. The computermay determine or adjust a resection depth based on the first and secondsigned distances. The computer may also generate resection data usingthe resection depth, the resection data configured to be utilized by thenavigation system during the arthroplasty procedure.

B. Avoiding Anterior Shaft Notching

Once the preoperative planning has resulted in proposed bone resectionsas described above in Subsection A of this Detailed Description, theassociated orientation of the candidate femoral implant model can bechecked to see if notching of the anterior femoral cortex will occur. Intotal knee arthroplasty preoperative planning, anterior femoral cortexnotching 390 occurs when the femoral implant model 320 is preoperativelyplanned such that the top edge 400 of the anterior flange 402 sits deepinto the anterior femoral cortex 404 of the patient femur model 226.FIGS. 20A and 20B are, respectively, an anterior distal view and asagittal cross sectional view of the femoral implant model 320positioned on the patient femur model 226 such that the anterior femoralcortex 404 is notched. Where the actual femoral implant is implanted asindicated in FIGS. 20A and 20B, the indicated notching 390 of thefemoral cortex 404 would be an undesirable surgical outcome as thenotching creates stress concentrations in the anterior femoral cortexthat can lead to fracture of the femoral shaft or supracondylarfractures.

As illustrated in FIG. 21, a coordinate system 408 can be establishedfor the patient femur model 226, wherein the X-axis will be in themedial-lateral direction with the +X-axis pointing towards the lateralfemur, the Y-axis will be in the anterior-posterior direction with the+Y-axis pointing towards the posterior femur, and the Z-axis will be inthe superior-inferior direction with the +Z direction pointing towardsthe proximal femur.

FIGS. 22A-22C are, respectively, posterior, sagittal-posterior, andsagittal views of a candidate femoral implant model 320 with an outline410 of a haptic object superimposed on the femoral implant model 320.The candidate femoral implant model 320 includes an anterior boneresection contact surface 412 on an anterior flange portion 414 of thefemoral implant model 320. The anterior bone resection contact surface412 of the model 320 and an actual femoral implant are substantiallyplanar and configured to make substantially planar surface contact withan anterior bone resection surface generated in the actual patient boneduring the arthroplasty procedure.

As seen in FIGS. 22B and 22C, the haptic object 410 is generallyco-planar with the planar contact surface 412 of the anterior flangeportion 414 of the femoral implant model 320. Thus, the haptic object410 is essentially a planar extension of the planar contact surface 412of the anterior flange portion 414 of the femoral implant model 320.

As illustrated in FIG. 23, which is an enlarged anterior view of asuperior edge of the anterior flange portion 414 of the femoral implantmodel 320 and a superior boundary 418 of the haptic plane 410, a seriesof equally-spaced reference points 416A-416K extend along the superiorboundary 418 of the haptic plane. Reference points 416A and 416K are endpoints of the series of equally-spaced points 416A-416K. It is notedthat the number of points 416 along the superior boundary 418 may bemore or less than depicted in FIG. 23. More points 416 may increase theaccuracy of the notch assessment, but increasing the points 216 alsoincreases computing time. As discussed below, these reference points areused to evaluate the depth of anterior femoral notch 390 which ismeasured along the femur anatomical Y direction according to thecoordinate system of FIG. 21.

The number of reference points 416A-416K employed in the algorithmdepends on the following assumptions in conjunction with the size of thecandidate femoral implant model 320. For example, the chance of error inidentifying anterior femoral cortex notching increases with a decreasein radius of curvature of the anterior femoral cortex or with a decreasein the number of equally-spaced reference points 416A-416K.Unfortunately, simply increasing the number of equally-spaced referencepoints 416A-416K to reduce the point-spacing can have an adverse impacton the performance of the algorithm.

The cortex region is convex in nature with a varying radius of curvaturemoving medial to lateral along the femur. Accordingly, assuming thesmallest radius of curvature the algorithm may encounter will be 10 mm,and the minimum clinically relevant notch depth a surgeon may feel is0.125 mm, these two assumptions yield a minimum point-spacing of 3.15mm. Thus, as can be understood from FIG. 24, which is a schematicdepiction of an anterior femoral cortex notch situation 390 with aradius of 10 mm, the superior edge 418 of the haptic plane 410 with apair of reference points 416B-416C spaced-apart 3.15 mm, the pair ofpoints 416B-416C being just below (e.g., 0.001 mm) the notch, and thecandidate femoral implant model 320 having an anterior flange 414 with asuperior edge that has a largest possible size of 37.53 mm, the maximumnumber of points possible with a point-spacing less than or equal to3.15 mm is approximately 12 (i.e., 37.53/3.15=11.91≈12). Thus, as shownin FIG. 23, 12 reference points 416A-416K are employed. Of course, whereanterior flanges of other sizes are employed, the number of referencepoints employed in the algorithm may be less than or greater than 12equally-spaced reference points.

As can be understood from FIG. 23 and also FIGS. 25A and 25B, which arecross-sectional sagittal views of the patient femur model 226 and thecandidate femoral implant model 320 thereon in no-notching and notchingarrangements, respectively, the algorithm projects a vector 420 alongthe femur anatomical Y axis of the coordinate system 408 from each ofthe reference points 416A-416K to the surface boundary of the patientfemur model 226. A state of “notching” is determined to occur when thefollowing two conditions are fulfilled: (1) the length of the smallestof these vectors 420 is equal to or greater than 0 mm; and (2) thedirection of the smallest of these vectors 420 is opposite to anatomical+Y of the coordinate system 408, as illustrated in FIG. 25B. Once astate of “notching” is identified, the system 100 may provide an audioand/or visual warning and the state if “notching” may be displayed toappear much like any of FIGS. 20A and/20B on the display 56.

A state of “no notching” is determined when the following two conditionsare fulfilled: (1) the length of the smallest of these vectors 420 isgreater than 0 mm; and (2) the direction of the smallest of thesevectors 420 is the same as anatomical +Y of the coordinate system 408,as indicated in FIG. 25A. Once a state of “no notching” is identified,the system 100 may provide an audio and/or visual indication and thestate of “no notching” may be displayed to appear much like FIG. 25A ora non-notching version of FIG. 20A on the display 56.

Once a surgeon has approved, or modified and approved, the proposed boneresections as preoperatively planned according to Subsection A of thisDetailed Description and verified that there is no unacceptable notchingof the anterior femoral cortex associated with the preoperativelyplanned bone resection, the lack of unacceptable notching having beenverified according to Subsection B of this Detailed Description, thepreoperatively planned bone resections can be intraoperativelyregistered with the patient's actual bone and the surgical system 100 aswill now be described.

Once it is determined if notching occurs or not, the surgical system 100may generate implant component position and orientation data based onthe determined position and orientation of the femoral implant modelrelative to the patient femur model. The implant component position andorientation data may be employed in setting haptic boundaries forcontrolling a haptic device 60 or surgical robot during the arthroplastyprocedure. Thus, the steps described herein may describe a method ofgenerating implant position and orientation data for use in planning anarthroplasty procedure on a patient bone.

Other methods of notch assessment are possible such as, for example, ifa line extending between 416A and 416K along the superior boundary 418of the haptic plane intersects the solid bone of the patient femur model226. In such a case, notching occurs if the line does intersect thesolid bone of the patient femur model 226. Conversely, notching does notoccur if the line does not intersect the solid bone of the patient femurmodel 226.

C. Checking the Closeness of Checkpoints to Resection Planes

In certain robotic assisted orthopedic procedures, intraoperativeregistration of the patient bone with the robotic system 100 may involvethe use of removable checkpoints positioned on the patient's boneyanatomy. As seen in FIG. 26A, which is a side view of a checkpoint 600,the checkpoint 600 is similar to bone anchor or screw for impacting intothe bone of the patient. The checkpoint 600 may include a head end 602at a proximal end and shaft 604 extending distally from the head end602. The head end 602 may include an opening or divot 606 having aninner surface 608 that is conical or frusto-conical, among other shapes.The divot 604 provides for a mechanical interface with a registrationinstrument (e.g., navigation probe). The shaft 604 of the checkpoint 600may include threads 610 and a distal tip 612 for rotationally drivingthe checkpoint 600 into a bone.

As seen in FIG. 26B, which is side view of a patient's bone (tibia 10,femur 11) undergoing a checkpoint identification step in a total kneearthroplasty, the distal end 504 of the navigation probe 55 may beplaced in contact with the inner surface 608 of the divot 606 on thehead end 602 of the checkpoint 600 in order to positionally relate,reference, or register the femur 11 relative to other components of thesurgical system 100 via the detection device 44 of the navigation system42, as seen in FIG. 1. During checkpoint identification, the distal end504 of the navigation probe 55 may “bottom out” at a predeterminedlocation within the divot 606 such that the surgical system 100 canaccurately position the checkpoint 600 and, thus, the patient femur 11relative to the instrument 55 and any other devices in the surgicalsystem 100, such as any computerized patient models 226 of the bone 11depicted on the display 56. Aspects of checkpoint identification andcheckpoints 600, among other topics, are discussed in U.S. patentapplication Ser. No. 11/750,807, entitled “System and method forverifying calibration of a surgical device,” filed May 18, 2007, whichis incorporated by reference in its entirety into the presentapplication.

Each checkpoint 600 used during a surgical procedure must be positionedon the patient bone (e.g., femur 11) such that it is accessible duringthe procedure given the particular surgical approach. Additionally, eachcheckpoint 600 must be positioned such that it does not interfere withthe procedure or the tools used during the procedure. For example, thecheckpoint 600 should be located on a portion of the bone such that itwill not interfere with a cutting device or be removed by a resection.The subsequently described methods and systems may aid in preoperativelydetermining the locations or positions of checkpoints 600 that will notinterfere with the cutting tool and that will not be removed during theresections.

Reference is made to FIGS. 26C-26E, which are, respectively, the patientfemur model 226 depicting the location of an implant component 320 and acheckpoint 600, a patient tibia model 224 depicting a location of animplant component 300 and a checkpoint 600, and a flow chart indicatingsteps in the preoperative checkpoint location verification process 360.During preoperative planning of an arthroplasty procedure, the surgeonor medical professional may identify the locations of the checkpoints600 on the patient bone models 224, 226 [block 362]. Alternatively, thelocations of the checkpoints may be automatically positioned on thepatient bone models 224, 226. Preoperative planning continues asdescribed in the previous sections by planning the types, positions, andorientations of implant components 320, 300 and resection planes 334,306 relative to the patient bone models 224, 226 [block 364]. Thecheckpoint location verification process 360 may work in conjunctionwith the planning of the implant components 320, 300 by alerting theplanner (e.g., surgeon) when the implant component 320, 300 is plannedsuch that the associated resection plane will interfere with thecheckpoint 600 in a certain way that will require an alternativelocation for the checkpoint 600 or an alternative placement/orientationof the implant component 320, 300. In certain instances, it may beeasier to modify the location and placement of the checkpoints 600 thanto modify the location and orientation of a desired implant component320, 300. Therefore, the planner may alter the location of thecheckpoints 600 such that the checkpoints 600 no longer interfere withthe resection planes.

Continuing on, once the resection planes 334, 306 are identified at[block 364], a normal line (N) is identified for each of the resectionplanes [block 366], as shown in FIGS. 26F and 26G, which are,respectively, a pair of sagittal schematic views of femur resections 334and tibial resections 306 with checkpoints 600 positioned relative tothe resections 334, 306. As seen in FIGS. 26F-26G, the normal lines (N)are perpendicular to the resection planes 334, 306. Next, the shortestsigned distance vector (d) is determined between the checkpoint 600 andeach of the resection planes. FIGS. 26F-26G depict the shortest signeddistance vector (d) in the sagittal view since the resection planes 334,306 are orthogonal to this view, which results in the planes 334, 306appearing as lines instead of planes.

While the shortest signed distance vector is displayed visually, theshortest signed distance vector (d) may be computed without beingdisplayed visually. Additionally, while the shortest signed distancevector (d) in FIGS. 26F-26G is only depicted for the anterior resection334 a, the shortest signed distance vector (d) may be determined,calculated, or identified for each of the resection planes 334 (e.g.,distal resection plane 334 d, posterior resection plane 334 p,distal-anterior chamfer resection plane 334 da, and distal-posteriorchamfer resection plane 334 dp).

It is noted that the shortest signed distance vector (d) includes amagnitude or distance and a three-dimensional direction. The shortestsigned distance vector (d) may be defined as the shortest perpendiculardistance between the checkpoint 600 and a corresponding point on theassociated resection plane(s) of the implant component that iscoextensive with the resected surface 334 of the bone. That is, theshortest signed distance vector (d) is perpendicular to the resectionplane(s) and parallel with the normal line(s) (N). As seen in FIG. 26G,the shortest signed distance vector (d4) extends to a point on theassociated resection plane of the implant component that is coextensivewith and positioned above the resection surface 334 p.

In certain embodiments, a shortest distance vector may be used insteadof a shortest signed distance vector (d). That is, in this particularembodiment, the shortest distance vector is not required to beperpendicular to the associated resection plane(s) of the implantcomponent or the resected bone surfaces. Instead, the shortest distancevector may simply be the shortest distance vector between the checkpoint600 and either a point on the resection plane or the resected surface334, 306 of the bone. In some cases, the shortest distance vector may beperpendicular to the resected surface 334, 306 or the resection plane.Using a shortest distance vector may, in some instances, result in amagnitude that is less than a magnitude calculated with a shortestsigned distance vector (d).

As discussed previously, the shortest distance vector may extend fromthe checkpoint 600 to the associated resection plane(s) or the virtuallyresected bone surface 334, 306. Additionally or alternatively, theshortest distance vector may extend from the checkpoint 600 to a hapticobject that represents the allowable cutting perimeter of a cutting tool(e.g., saw blade). The haptic object is planar in geometry and is notinfinite (i.e., unlike a resection plane). It is located at the intendedresection plane but has a finite area. The perimeter of the hapticobject constrains the saw blade to the intended cut and is designed tobe large enough to include the saw (e.g. a blade of 25 mm wide will havea haptic object of at least 25 mm wide), shaped to remove at least thebone amount necessary to place the implant at that location, and isshaped to protect soft tissues (i.e., not infinite).

The following discussion will take place with a discussion of theshortest signed distance vector (d), but the discussion is equallyapplicable to a shortest distance vector as described in the previousparagraphs.

Referring back to FIG. 26E, the next step in the checkpoint locationverification process 360 is to ask whether the normal line (N) and thedistance vector (d), for each respective resection plane 344, arepointing in the same direction [block 370]. If the normal line (N) andthe distance vector (d) are pointing in the same direction [block 372],then the resection plane is considered to be sitting “proud” withrespect to the checkpoint 600. In this case, the following function iscomputed: if the magnitude of the distance vector (d) is less than orequal to 4.50 mm, then the location of the checkpoint 600 is too closeto the resection plane 334 and the system alerts the planner with awarning [block 376], which may be an audio and/or visual indication thatthe location of the checkpoint 600 should be modified. If the normalline (N) and the distance vector (d) are pointing in the same direction,but the magnitude of the distance vector (d) is more than 4.50 mm, thenthe location of the checkpoint 600 does not need to be modified.

If the normal line (N) and the distance vector (d) are not pointing inthe same direction (i.e., pointing in opposite directions), then theresection plane 334 is located “deep” with respect to the checkpoint 600and, thus, the checkpoint 600 would interfere with the resection or beresected off of the bone during the arthroplasty procedure [block 374].In such a case, the system alerts the planner with a warning [block376], which may be an audio and/or visual indication that the locationof the checkpoint 600 should be modified. Information associated withthe checkpoint position/orientation, as well as the position/orientationof the resection planes may be used by the surgical system 100 togenerate resection and checkpoint positioning data, which may beemployed during the arthroplasty procedure with a haptic device 60 orsurgical robot. Thus, the steps in the method described herein maydescribe a method of generating resection plane and checkpointpositioning data for use in planning an arthroplasty procedure on apatient bone.

Alternative methods may be used to determine whether or not the locationof the checkpoint 600 is situated “deep” or “proud” without using thenormal line (N). For example, the shortest signed distance vector (d)from the checkpoint 600 to the resection plane may be determined. Apositive sign may indicate the checkpoint 600 is “proud” of the plane.Conversely, a negative sign for the shortest signed distance vector (d)may indicate the checkpoint 600 is “deep” or recessed from the plane.

As seen in FIG. 26F, regarding the femur resections 334, the distancevector (d) from the checkpoint 600 to the anterior resection plane 334 apoints in a first direction (i.e., towards the patient bone), and thenormal line (N) for the anterior resection plane 334 a points in asecond direction (i.e., away from the patient bone), which is oppositeof the first direction. Thus, as seen in [block 370] and [block 374],the resection plane is located deep with respect to the checkpoint 600and the checkpoint 600 would interfere with the resection (e.g., contactthe cutting tool) or be resected off of the bone during the arthroplastyprocedure. Because of this, an alert or warning is signaled to theplanner by the system to consider an alternative placement of thecheckpoints 600 or implant component 320, 300. Once a determination ismade that the checkpoint 600 would interfere with a cutting tool or beresected off of the bone, there may not be a need to compute theshortest signed vector (d) for other resection surfaces 334 da, 334 d,334 dp, 334 p. Such a computation may, however, be computed in certaininstances.

Regarding the tibial resection 306 in FIG. 26F, the distance vector (d)from the checkpoint 600 to the proximal tibial resection 306 points in afirst direction (i.e., towards the patient bone), and the normal line(N) for the resection 306 points in a second direction (i.e., away fromthe patient bone), which is opposite of the first direction. Thus, asseen in [block 370] and [block 374], the resection plane is located deepwith respect to the checkpoint 600 and the checkpoint 600 wouldinterfere with the resection (e.g., contact the cutting tool) or beresected off of the bone during the arthroplasty procedure. Because ofthis, an alert or warning is signaled to the planner by the system toconsider an alternative placement of the checkpoints 600 or implantcomponent 320, 300.

Referring to the femur resection portion of FIG. 26G, the distancevector (d) from the checkpoint 600 to the anterior resection plane 334 apoints in a first direction (i.e., away from the patient bone), and thenormal line (N) for the anterior resection plane 334 a also points inthe first direction (i.e., away from the patient bone). Since the normalline (N) and the directional portion of the distance vector (d) pointsin the same direction, the checkpoint location verification process 360continues with [block 372]. According to this step in the process, themagnitude or distance portion of the distance vector (d) is analyzedaccording to the following equation: is magnitude of distance vector (d)less than or equal to 4.50 mm, if so, then the checkpoint 600 is tooclose to the resection plane 334 and an alert or warning is sent by thesystem to the planner [block 376]. If the magnitude of the distancevector (d) is greater than 4.50 mm, then the checkpoint 600 isadequately positioned for the arthroplasty procedure.

As seen with reference to the femur resections 334 of FIG. 26G,additional distance vectors (d1), (d2), (d3), (d4) may be analyzed inthe same way that the original distance vector (d) was analyzed. As seenin the figure, all distance vectors (d1), (d2), (d3), (d4) point in thesame direction as their respective normal lines (N). Thus, each distancevector (d1), (d2), (d3), (d4) is analyzed with respect to [block 372] todetermine if the checkpoint 600 is too close to the respective resectionplane 334 da, 334 d, 334 dp, 334 p. If one or more of the distancevectors (d1), (d2), (d3), (d4) are less than or equal to 4.50 mm fromtheir respective resection plane 334 da, 334 d, 334 dp, 334 p, then thelocation of the checkpoint 600 must be modify, adjusted, or moved suchthat it satisfies the condition in [block 372], while not causing any ofthe other distance vectors (d1), (d2), (d3), (d4) to be less than orequal to 4.50 mm from the resection plane 334 a, 334 da, 334 d, 334 dp,334 p.

The rationale for the 4.50 mm threshold in [block 372] is illustrated inthe table 650 of FIG. 26H. The table 650 outlines various error sourcestaken into account for the 4.50 mm threshold of the checkpoint 600 beingtoo close to the resection plane. The posterior cut system error in line1 of the table 650 refers to the maximum system error associated with aposterior resection in anatomical Y-direction (e.g., anterior-posteriordirection in FIGS. 26F-26G). The maximum system error is the maximumpermitted error or deviation that the system 100 will permit the user tomake while conducting the posterior cut. In this particular instance,the maximum system error associated with the posterior cut in theanatomical Y-direction is illustrated by reference X1.

The distal cut system error in line 2 of the table 650 of FIG. 26Hrefers to the maximum system error associated with a distal resection inanatomical Z-direction (e.g., distal-proximal direction in FIGS.26F-26G). The maximum system error is the maximum permitted error ordeviation that the system 100 will permit the user to make whileconducting the distal cut. In this particular instance, the maximumsystem error associated with the distal cut in the anatomicalZ-direction is illustrated by reference X2.

The anterior chamfer system error due to the posterior cut, in line 3 ofthe table 650 in FIG. 26H, refers to the maximum system error associatedwith the anterior chamfer cut due to the maximum error associated withthe posterior cut, discussed in reference to line 1 of the table 650. Asseen in FIG. 26I, which is a sagittal view of the femur resections 334in a first position shown in solid line and a second position shown indotted lines after being translated, when the posterior cut istranslated by in the anatomical Y-direction, the anterior chamfer cutmoves closer to the checkpoint by an amount illustrated by reference X3.

The anterior chamfer system error due to the distal cut, in line 4 ofthe table 650 in FIG. 26H, refers to the maximum system error associatedwith the anterior chamfer cut due to the maximum error associated withthe distal cut, discussed in reference to line 2 of the table 650. Asseen in FIG. 26J, which is a sagittal view of the femur resections 334in a first position shown in solid line and a second position shown indotted lines after being translated, when the distal cut is translatedin the anatomical Z-direction, the anterior chamfer cut moves closer tothe checkpoint by an amount illustrated by reference X4.

The profile error, illustrated by reference X5, in line 5 of the table650 of FIG. 26H is the maximum profile error associated with theanterior chamfer cut. Profile error is the resection error associatedwith anterior, anterior chamfer, and posterior chamfer cuts afteraligning the surgeon's distal and posterior cuts with planned distal andposterior cuts. Thus, it is an error relative to distal and posteriorcuts which are assumed to be primary and secondary data for alignmentpurposes.

As an example, suppose a surgeon has finished all five cuts on a femurand begins trialing. Assume the distal cut is 1 mm prouder than plannedand the posterior cut is 1 mm deeper than planned. When the surgeonbegins trialing, the surgeon zeroes out the distal cut error by ensuringthe implant component sits flushed with the resected bone on the distalplane and ensures the same on the posterior cut. With this, the surgeontransfers all of the distal and posterior cut errors onto the anterior,anterior chamfer, and posterior chamfer cuts. This type of error may becontrolled by setting a bilateral tolerance band of 1.5 mm, for example,around the cuts. That is, all anterior, anterior chamfer, and posteriorchamfer cuts will be within ±1.5 mm about the preoperatively plannedlocation when distal and posterior cuts are zeroed out.

At line 6 of the table 650 of FIG. 26H, the root sum of the squares,illustrated by reference X6, which is a combined error given a list ofcontributing variables, is computed for the anterior chamfer error dueto the posterior cut, the anterior chamfer error due to the distal cut,and the profile error. Using the values provided in the table 650, theroot sum of the squares equates as follows:RSS=SQRT((X3)^2+(X4)^2+(X5)^2)=X6.

At lines 7 of the table 650 of FIG. 26H, the distance of the blade of acutting tool from the TCP inside a checkpoint 600 is illustrated byreference X7, which in certain instances may be about 2.87 mm. Thisvalue is the shortest distance the blade of a cutting tool could be fromthe center point of the divot 606 (as seen in FIG. 26A) of thecheckpoint 600 without contacting the checkpoint 600. Thus, the cuttingtool must be spaced at least 2.87 mm, in this instance, from the toolcenter point (TCP) of the checkpoint 600 in order for the tool to notinterfere or contact the checkpoint 600. For this calculation, it isassumed that the femoral checkpoint 600 is positioned on the femoralsurface that is angled at about forty-five degrees to the sagittalplane.

As seen on the table 650 of FIG. 26H, the total threshold distance X8 iscalculated by combining or adding the root sum of the squares X6, online 6, with the blade distance factor X7, on line 7.

Referring to the tibial chart 652 of FIG. 26H, the tibial proximal cuterror is illustrated by reference Y1, at line 1. The tibial proximal cuterror is the maximum system error associated with the proximal resectionin the anatomical Z-direction (e.g., distal-proximal direction). Thatis, Y1 is the maximum allowable error that is permissible for a user inconducting the proximal resection of the tibia. In line 2 of the tibialchart 652, the blade distance factor is illustrated by reference Y2 fora tibial checkpoint 600. Given the values in lines 1 and 2 of the tibialchart 652, the sum of these values is illustrated by reference Y3 and isthe total threshold distance.

The larger of the femoral and tibial checkpoint thresholds may berounded up to 4.50 mm and used in the checkpoint location verificationprocess 360 described herein.

III. Intraoperative Cartilage Surface Registration

In one embodiment, the three dimensional patient bone models 224, 226are generated from CT images of the patient's actual femur and tibia. Inother embodiments, the patient bone models 224, 226 are generated fromother types of medical images, such as CT with contrast injection, MRI,X-ray, or etc. Some of these imaging modalities will depict thepatient's cartilage (e.g., CT with contrast and MRI) and result inpatient bone models that reflect the presence of the patient's cartilageand other imaging modalities (e.g., straight CT) will not, resulting inpatient bone models that do not reflect the presence of the patientscartilage and are reflective of only the patient's actual cortical orouter bone surface.

In situations where straight CT images are used to generate the threedimensional patient bone models 224, 226 because CT has advantages overother imaging modalities, such as MRI, in the areas of resolution andspeed, for example, the resulting CT based bone models will not reflectthe patient's cartilage surface. That is, the bone models are bone-onlymodels. Since the above-described preoperative planning involvesdetermining bone resection depth off of the bone-only condylar surfacesof the patient bone models 224, 226, which do not reflect the patient'scartilage condylar surfaces, and since the surgical implantation of theactual femoral and tibial implants need to be positioned such that theirrespective condylar surfaces are located in a position that replicatesthe patient's native cartilage condylar surfaces being replaced as partof the total knee arthroplasty procedure, the thickness of the cartilageneeds to be accounted for in the surgery.

One way of accounting for the lack of cartilage representation in bonemodels 224, 226 generated via CT and used in the above-describedpreoperative planning methodology is to move the preoperatively plannedfemur and tibia bone resection planes 334, 302 respectively distally andproximally an amount equivalent to the cartilage thickness, as can beunderstood from FIGS. 27A and 27B, which are, respectively, a sagittalview of the femoral implant and patient bone models 320, 226 aspreoperatively planned and a sagittal view of the tibial implant andpatient bone models 300, 224 as preoperatively planned. As indicated bythe dashed arrows in FIG. 27A, the preoperatively planned location ofthe femoral implant condylar surface 332 moves distally to assume acartilage compensated location 332A of the femoral implant condylarsurface, and the preoperatively planned location of the femoralresection 334 moves distally to assume a cartilage compensated location334A of the femoral resection. The result of such an adjustment willcause the actual femoral implant to have its condylar surface located soas to act in place of the resected femoral cartilage condylar surface.

As shown by the dashed arrows in FIG. 27B, the preoperatively plannedlocation of the tibial implant condylar surface 304 moves proximally toassume a cartilage compensated location 304A of the tibial implantcondylar surface, and the preoperatively planned location of the tibialresection 306 moves proximally to assume a cartilage compensatedlocation 306A of the tibial resection. The result of such an adjustmentwill cause the actual tibial implant to have its condylar surfacelocated so as to act in place of the resected tibial cartilage condylarsurface.

In one embodiment, the cartilage compensation can be made by making themoves shown in FIGS. 27A and 27B according to an estimated value forcartilage thickness. For example, the femoral and tibia preoperativelyplanned resections could be moved their respective directions anestimated cartilage thickness of, for example, 2 mm.

In another embodiment, the cartilage compensation can be made during anintraoperative registration process as will now be discussed. Asdiscussed above with respect to FIG. 1, during the actual surgery, theactual patient bones 10, 11 are positionally registered to thecorresponding patient bone models 224, 226 via navigation markers 46affixed to the patient bones 10, 11 and detected via the detectiondevice 44 of the navigation system 42. On account of the intraoperativeregistration of the actual bones 10, 11 to the bone models 224, 226, thesystem 100 knows where the bone model condylar surfaces are relative tothose of the actual bones 10, 11. However, since the bone models are theresult of CT imaging, the cartilage condylar surfaces were not part ofthe preoperative planning, and the system 100 does not know where thecartilage condylar surface is in relation to those of the actual bonesor bone models. Registration of the cartilage can remedy this situation.

FIGS. 28A and 28B are, respectively, an axial or transverse distal viewand a coronal posterior view of the patient femoral model 226 asdepicted on the display 56 of the system in FIG. 1. Landmark captureregions 500, 501 are highlighted on the model 226 in each view. Thelandmark capture regions pertain to regions on the actual patient femur11 that can be identified by the surgeon intraoperatively.

FIGS. 29A and 29B are, respectively, enlarged views of the landmarkcapture regions 500, 501 of FIGS. 28A and 28B, respectively, wherein aseries of registration points 502 are depicted on each capture region.In one embodiment, each region 500, 501 has ten points 502 thereon, andin other embodiments, the number of points 502 can be greater or lessthan 10.

As can be understood from FIG. 1 and FIGS. 29A and 29B, a distal end 504of the navigation probe 55 or the distal end 504 of a capture probeextending from the free end of the end effector of the haptic device 60(i.e., the part of the haptic device 60 that is shown as occupied by thesurgical tool 58 in FIG. 1) is guided by the surgeon to contact theactual cartilage condyle surface of the patient's actual femur 11intraoperatively at locations the surgeon believes to be the same as thepoints 502 in regions 500 and 501 shown on the display in FIGS. 29A and29B. Each time the surgeon touches the cartilage condylar surface of thepatient's actual femur 11 in a location believed to correspond with oneof the points 502 displayed on the display 56, the surgeon makes aninput into the system 100, which then registers that actual cartilagepoint location and the corresponding point 502 show on the display 56.This process is repeated until all ten points 502 are registered tocorresponding point locations on the cartilage condylar surface of theactual patient femur 11. While the process is described as registeringindividual points on the cartilage surface that correspond with specificpoints shown on the bone models, the system 100 may alternativelydisplay a target region only and not depict individual points forcapturing.

As a result of the capturing process, the cartilage condylar surface ofthe actual patient femur is now registered to the patient femur model226 on account of the patient femur model being already registered tothe actual patient femur 11. As an alternative to individually inputtingeach point 502 into the system 100 with separate discreet actions by thesurgeon or member of the surgical team, the capture process may beinitiated by a single input (e.g., button click on screen, foot pedalinput, button press on navigation probe 55), then the surgeon may“paint” the region 500, 501 while the system automatically inputs thelocation of the distal end 504 of the navigation probe 55 on the bonesurface. Thus, the system may collect the ten points in a short amountof time with only a single input signal provided by the surgeon orsurgical team.

Returning to FIG. 27A with the cartilage condylar surface beingregistered relative to the patient bone model 226 as described and withthe location of the cartilage condylar surface being represented by thedashed line 332A, the system 100 moves the implant condylar surface 332distally to positionally coincide with the cartilage condylar surfaceline 332A, thereby pulling the preoperatively planned resection line 334to the intraoperatively adjusted resection line 334A. Thus, thepreoperatively planned resection line has been adjusted intraoperativelyvia registration of the cartilage condylar surface of the actual patientfemur 11 to the patient femur model 226 via the described registrationprocess.

Once the cartilage condylar surface is registered, the preoperativelyplanned resection may be adjusted or determined by moving the implantcondylar surface distally an amount that equals the difference betweenthe articular surface of the three-dimensional bone-only model and themapped cartilage surface in a particular direction.

While the registration line for the cartilage condylar surface 332A isdepicted in FIG. 27A as being a line, in some embodiments, the cartilageoffset information may simply be in the form of a point or otherreference that is offset from the condylar surface of the femur model226 by the registered thickness of the cartilage region 500 beingregistered. In certain embodiments, the system 100 may only depict asingle point that is the lowest/most distal/most posterior/most proximaldepending on the particular bone region of interest. In certainembodiments, all or a portion of all of the points 502 may be used tointerpolate a surface and the system 100 may move the implant condylarsurface 332 to the interpolated surface.

Once the resection depth is adjusted based on the cartilage thickness,the surgeon may accept the change or modify the implant plan.

While the preceding cartilage registration discussion takes place in thecontext of the femoral intraoperative cartilage registration andresection adjustment, the preceding discussion is equally applicable tothe tibial intraoperative cartilage registration and resectionadjustment, as can be understood from a comparison of FIGS. 27A, 28A and29A to FIGS. 27B, 28B and 29B.

On account of having the preoperatively planned resections adjusted toaccount for cartilage thickness via the above-described cartilageregistration process, the implanted implants may have their respectivecondylar surfaces located so as to act in place of the resectedcartilage condylar surfaces. In other embodiments, the implantedimplants may have only one condylar surface (e.g., medial or lateral)located so as to act in place of the resected cartilage condylarsurface. In other embodiments, the implanted implants may not have anycondylar surface (e.g., medial or lateral) located so as to act in placeof the resected cartilage condylar surface.

The intra-operative cartilage registration process may be described as aprocess or method of generating resection data for use in planning aknee arthroplasty. Since the patient bone model 226, 224 may depict boneonly, in certain embodiments, and the actual patient bone may be coveredat least partially in cartilage, intra-operative registration of thecartilage may provide insight into an amount of adjustment to theresection depth, which may be determined preoperatively with or withoutadditional or alternative considerations of cartilage.

The process or method may generally be described as follows. A computerof the system may receive a three-dimensional patient bone model 226,224 (e.g., femur model, tibia model) generated from medical images(e.g., CT, MRI, X-ray) of the patient bone (e.g., femur, tibia). Thethree-dimensional patient bone model 226, 224 may include a bone modelsurface corresponding to the shape and patient-specific contours of theactual patient bone. The three-dimensional patient bone model 226, 224may be correlated with a position and orientation of the actual patientbone via the tracking and navigation system described in reference toFIG. 1. The three-dimensional patient bone model 226, 224 may bepositioned in a three-dimensional coordinate system or space.

The method or process may also include identifying a location of a firstplurality of points 502 within a target region 500, 501 on the bonemodel surface of the three-dimensional patient bone model 226, 224 forintra-operative registration by a surgeon with a distal end 504 of anavigation probe 55. The method or process may also include receivinglocation data for a second plurality of points based on theintra-operative registration of the cartilage on the actual, physicalpatient bone in locations corresponding to the first plurality of points502 on the bone model surface of the three-dimensional bone model 226,224.

The method or process may also include determining a resection depthbased on a comparison between the location data for the second pluralityof point and the location of the first plurality of points on the bonemodel surface. The method or process may also include generatingresection data using the resection depth. The resection data may beemployed as a haptic boundary for controlling the surgical robot ofFIG. 1. Additionally or alternatively, the resection data may beutilized by a surgical robot during the arthroplasty procedure.Additionally or alternatively, the resection data may be utilized by anavigation system during the arthroplasty procedure. The navigationsystem may operate in conjunction with an autonomous robot or asurgeon-assisted device in performing the arthroplasty procedure. Anautonomous robot, such as a cutting device with at least two degrees offreedom (e.g., rotating burr and translation capabilities) may performthe arthroplasty procedure with the resection data utilized as a toolpath for performing a resection. A surgeon-assisted device, such as thehaptic device 60 described herein or a cutting tool with at least onedegree of freedom (e.g., rotating burr moved or translated by asurgeon), may perform the arthroplasty procedure with the resection databeing a virtual or haptic boundary for controlling or limiting certainmovements of the cutting tool (e.g., depth of resection).

An example of the method described herein may involve generatingresection data for use in planning an arthroplasty procedure on apatient bone covered at least partially in cartilage. The method mayinclude a computer receiving a three-dimensional patient bone modelincluding a bone model surface, the three-dimensional patient bone modelcorrelated with a position and orientation of the patient bone via anavigation system. The three-dimensional patient bone model being in athree-dimensional coordinate system. The computer may identify a targetregion on the bone model surface of the three-dimensional patient bonemodel for intra-operative registration. The computer may also receivelocation data for a first plurality of points based on theintra-operative registration of the cartilage on the patient bone inlocations corresponding to points within the target region on the bonemodel surface of the three-dimensional bone model. The computer may alsodetermine a resection depth based at least in part on the location datafor the first plurality of point. The computer may also generateresection data using the resection depth, the resection data configuredto be utilized by the navigation system during the arthroplastyprocedure.

Referring to FIG. 30, a detailed description of an example computingsystem 1300 having one or more computing units that may implementvarious systems and methods discussed herein is provided. The computingsystem 1300 may be applicable to any of the computers or systemsutilized in the preoperative planning of the arthroplasty procedure, andother computing or network devices. It will be appreciated that specificimplementations of these devices may be of differing possible specificcomputing architectures not all of which are specifically discussedherein but will be understood by those of ordinary skill in the art.

The computer system 1300 may be a computing system that is capable ofexecuting a computer program product to execute a computer process. Dataand program files may be input to the computer system 1300, which readsthe files and executes the programs therein. Some of the elements of thecomputer system 1300 are shown in FIG. 30, including one or morehardware processors 1302, one or more data storage devices 1304, one ormore memory devices 1308, and/or one or more ports 1308-1310.Additionally, other elements that will be recognized by those skilled inthe art may be included in the computing system 1300 but are notexplicitly depicted in FIG. 30 or discussed further herein. Variouselements of the computer system 1300 may communicate with one another byway of one or more communication buses, point-to-point communicationpaths, or other communication means not explicitly depicted in FIG. 30.

The processor 1302 may include, for example, a central processing unit(CPU), a microprocessor, a microcontroller, a digital signal processor(DSP), and/or one or more internal levels of cache. There may be one ormore processors 1302, such that the processor 1302 comprises a singlecentral-processing unit, or a plurality of processing units capable ofexecuting instructions and performing operations in parallel with eachother, commonly referred to as a parallel processing environment.

The computer system 1300 may be a conventional computer, a distributedcomputer, or any other type of computer, such as one or more externalcomputers made available via a cloud computing architecture. Thepresently described technology is optionally implemented in softwarestored on the data stored device(s) 1304, stored on the memory device(s)1306, and/or communicated via one or more of the ports 1308-1310,thereby transforming the computer system 1300 in FIG. 30 to a specialpurpose machine for implementing the operations described herein.Examples of the computer system 1300 include personal computers,terminals, workstations, mobile phones, tablets, laptops, personalcomputers, multimedia consoles, gaming consoles, set top boxes, and thelike.

The one or more data storage devices 1304 may include any non-volatiledata storage device capable of storing data generated or employed withinthe computing system 1300, such as computer executable instructions forperforming a computer process, which may include instructions of bothapplication programs and an operating system (OS) that manages thevarious components of the computing system 1300. The data storagedevices 1304 may include, without limitation, magnetic disk drives,optical disk drives, solid state drives (SSDs), flash drives, and thelike. The data storage devices 1304 may include removable data storagemedia, non-removable data storage media, and/or external storage devicesmade available via a wired or wireless network architecture with suchcomputer program products, including one or more database managementproducts, web server products, application server products, and/or otheradditional software components. Examples of removable data storage mediainclude Compact Disc Read-Only Memory (CD-ROM), Digital Versatile DiscRead-Only Memory (DVD-ROM), magneto-optical disks, flash drives, and thelike. Examples of non-removable data storage media include internalmagnetic hard disks, SSDs, and the like. The one or more memory devices1306 may include volatile memory (e.g., dynamic random access memory(DRAM), static random access memory (SRAM), etc.) and/or non-volatilememory (e.g., read-only memory (ROM), flash memory, etc.).

Computer program products containing mechanisms to effectuate thesystems and methods in accordance with the presently describedtechnology may reside in the data storage devices 1304 and/or the memorydevices 1306, which may be referred to as machine-readable media. Itwill be appreciated that machine-readable media may include any tangiblenon-transitory medium that is capable of storing or encodinginstructions to perform any one or more of the operations of the presentdisclosure for execution by a machine or that is capable of storing orencoding data structures and/or modules utilized by or associated withsuch instructions. Machine-readable media may include a single medium ormultiple media (e.g., a centralized or distributed database, and/orassociated caches and servers) that store the one or more executableinstructions or data structures.

In some implementations, the computer system 1300 includes one or moreports, such as an input/output (I/O) port 1308 and a communication port1310, for communicating with other computing, network, or vehicledevices. It will be appreciated that the ports 1308-1310 may be combinedor separate and that more or fewer ports may be included in the computersystem 1300.

The I/O port 1308 may be connected to an I/O device, or other device, bywhich information is input to or output from the computing system 1300.Such I/O devices may include, without limitation, one or more inputdevices, output devices, and/or other devices.

In one implementation, the input devices convert a human-generatedsignal, such as, human voice, physical movement, physical touch orpressure, and/or the like, into electrical signals as input data intothe computing system 1300 via the I/O port 1308. Similarly, the outputdevices may convert electrical signals received from computing system1300 via the I/O port 1308 into signals that may be sensed as output bya human, such as sound, light, and/or touch. The input device may be analphanumeric input device, including alphanumeric and other keys forcommunicating information and/or command selections to the processor1302 via the I/O port 1308. The input device may be another type of userinput device including, but not limited to: direction and selectioncontrol devices, such as a mouse, a trackball, cursor direction keys, ajoystick, and/or a wheel; one or more sensors, such as a camera, amicrophone, a positional sensor, an orientation sensor, a gravitationalsensor, an inertial sensor, and/or an accelerometer; and/or atouch-sensitive display screen (“touchscreen”). The output devices mayinclude, without limitation, a display, a touchscreen, a speaker, atactile and/or haptic output device, and/or the like. In someimplementations, the input device and the output device may be the samedevice, for example, in the case of a touchscreen.

In one implementation, a communication port 1310 is connected to anetwork by way of which the computer system 1300 may receive networkdata useful in executing the methods and systems set out herein as wellas transmitting information and network configuration changes determinedthereby. Stated differently, the communication port 1310 connects thecomputer system 1300 to one or more communication interface devicesconfigured to transmit and/or receive information between the computingsystem 1300 and other devices by way of one or more wired or wirelesscommunication networks or connections. Examples of such networks orconnections include, without limitation, Universal Serial Bus (USB),Ethernet, Wi-Fi, Bluetooth®, Near Field Communication (NFC), Long-TermEvolution (LTE), and so on. One or more such communication interfacedevices may be utilized via the communication port 1310 to communicateone or more other machines, either directly over a point-to-pointcommunication path, over a wide area network (WAN) (e.g., the Internet),over a local area network (LAN), over a cellular (e.g., third generation(3G) or fourth generation (4G)) network, or over another communicationmeans. Further, the communication port 1310 may communicate with anantenna or other link for electromagnetic signal transmission and/orreception.

In an example implementation, patient data, bone models (e.g., generic,patient specific), transformation software, and other software and othermodules and services may be embodied by instructions stored on the datastorage devices 1304 and/or the memory devices 1306 and executed by theprocessor 1302. The computer system 1300 may be integrated with orotherwise form part of the surgical system 100.

The system set forth in FIG. 30 is but one possible example of acomputer system that may employ or be configured in accordance withaspects of the present disclosure. It will be appreciated that othernon-transitory tangible computer-readable storage media storingcomputer-executable instructions for implementing the presentlydisclosed technology on a computing system may be utilized.

In the present disclosure, the methods disclosed herein, for example,those shown in FIGS. 8, 10A-10C, 18-19, and 26E, among others, may beimplemented as sets of instructions or software readable by a device.Further, it is understood that the specific order or hierarchy of stepsin the methods disclosed are instances of example approaches. Based upondesign preferences, it is understood that the specific order orhierarchy of steps in the method can be rearranged while remainingwithin the disclosed subject matter. The accompanying method claimspresent elements of the various steps in a sample order, and are notnecessarily meant to be limited to the specific order or hierarchypresented.

The described disclosure including any of the methods described hereinmay be provided as a computer program product, or software, that mayinclude a non-transitory machine-readable medium having stored thereoninstructions, which may be used to program a computer system (or otherelectronic devices) to perform a process according to the presentdisclosure. A machine-readable medium includes any mechanism for storinginformation in a form (e.g., software, processing application) readableby a machine (e.g., a computer). The machine-readable medium mayinclude, but is not limited to, magnetic storage medium, optical storagemedium; magneto-optical storage medium, read only memory (ROM); randomaccess memory (RAM); erasable programmable memory (e.g., EPROM andEEPROM); flash memory; or other types of medium suitable for storingelectronic instructions.

While the present disclosure has been described with reference tovarious implementations, it will be understood that theseimplementations are illustrative and that the scope of the presentdisclosure is not limited to them. Many variations, modifications,additions, and improvements are possible. More generally, embodiments inaccordance with the present disclosure have been described in thecontext of particular implementations. Functionality may be separated orcombined in blocks differently in various embodiments of the disclosureor described with different terminology. These and other variations,modifications, additions, and improvements may fall within the scope ofthe disclosure as defined in the claims that follow.

In general, while the embodiments described herein have been describedwith reference to particular embodiments, modifications can be madethereto without departing from the spirit and scope of the disclosure.Note also that the term “including” as used herein is intended to beinclusive, i.e. “including but not limited to.”

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the exemplaryembodiments without departing from the scope of the present disclosure.

What is claimed is:
 1. A method of generating resection plane data foruse in planning an arthroplasty procedure on a patient bone, the methodcomprising: obtaining patient data associated with at least a portion ofthe patient bone, the patient data captured using a medical imagingmachine; generating a three-dimensional patient bone model from thepatient data, the patient bone model comprising a polygonal surfacemesh; identifying a location of a posterior point on the polygonalsurface mesh; creating a three-dimensional shape centered at or near thelocation; identifying a most posterior vertex of all vertices of thepolygonal surface mesh that are enclosed by the three-dimensional shape;using the most posterior vertex as a factor for determining a posteriorresection depth; and generating resection data using the posteriorresection depth, the resection data configured to be utilized by anavigation system during the arthroplasty procedure.
 2. The method ofclaim 1, wherein the three-dimensional patient bone model is athree-dimensional patient femur model.
 3. The method of claim 1, furthercomprising: identifying a first location of a first posterior point on afirst three-dimensional bone model; and mapping the first location onthe first three-dimensional bone model to the location on thethree-dimensional patient bone model, wherein the first location ispositionally correlated with the location.
 4. The method of claim 3,wherein the first three-dimensional bone model is a generic bone model.5. The method of claim 1, wherein the three-dimensional shape comprisesa sphere with a radius of about 7 mm.
 6. The method of claim 5, whereinthe radius is multiplied by a scaling factor.
 7. The method of claim 6,wherein the scaling factor is one of a medial-lateral oranterior-posterior size difference between the three-dimensional patientbone model and a generic bone model.
 8. The method of claim 1, whereinthe polygonal surface mesh is a triangular surface mesh.
 9. The methodof claim 1, wherein the three-dimensional shape comprises a sphere. 10.The method of claim 1, wherein the navigation system operates inconjunction with an autonomous robot or a surgeon-assisted device inperforming the arthroplasty procedure.
 11. A method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone, the method comprising: obtaining patient data associatedwith at least a portion of the patient bone, the patient data capturedusing a medical imaging machine; generating a three-dimensional patientbone model from the patient data, the patient bone model comprising apolygonal surface mesh; identifying a location of a distal point on thepolygonal surface mesh; creating a three-dimensional shape centered ator near the location; identifying a most distal vertex of all verticesof the polygonal surface mesh that are enclosed by the three-dimensionalshape; determining if the most distal vertex is too close to a boundaryof the three-dimensional shape; using the most distal vertex as a basisfor determining a distal resection depth if the most distal vertex isnot too close to the boundary of the three-dimensional shape; andgenerating resection data using the distal resection depth, theresection data configured to be utilized by a navigation system duringthe arthroplasty procedure.
 12. The method of claim 11, wherein thethree-dimensional shape comprises an ellipsoid oriented relative to thethree-dimensional patient bone model such that Rx extendsmedial-lateral, Ry extends anterior-posterior, and Rz extendsdistal-proximal.
 13. The method of claim 12, wherein Rx is about 7 mm,Ry is about 10 mm, and Rz is about 7 mm.
 14. The method of claim 13,wherein the most distal vertex is too close to the boundary of theellipsoid if a location of the most distal vertex is greater than 0.65for the ellipsoid function: f=x^2/a^2+y^2/b^2+z^2/c^2, wherein x is adifference in an x-direction between the first location and the mostdistal vertex, y is a difference in a y-direction between the firstlocation and the most distal vertex, z is a difference in a z-directionbetween the first location and the most distal vertex, a is Rx, b is Ry,and c is Rz.
 15. The method of claim 11, wherein the three-dimensionalpatient bone model is a three-dimensional patient femur model.
 16. Themethod of claim 11, wherein the three-dimensional shape comprises anellipsoid, a sphere, a prism, a cube, or a cylinder.
 17. The method ofclaim 11, wherein the navigation system operates in conjunction with anautonomous robot or a surgeon-assisted device in performing thearthroplasty procedure.
 18. A method of generating resection plane datafor use in planning an arthroplasty procedure on a patient bone, themethod comprising: obtaining patient data associated with at least aportion of the patient bone, the patient data captured using a medicalimaging machine; generating a three-dimensional patient bone model fromthe patient data, the patient bone model comprising a polygonal surfacemesh; identifying a location of a distal point on the polygonal surfacemesh; creating a first three-dimensional shape centered at or near thelocation; identifying a most distal vertex of all vertices of thepolygonal surface mesh that are enclosed by the first three-dimensionalshape; determining if the most distal vertex is located on anosteophyte; using the most distal vertex or an adjusted location of themost distal vertex as a basis for determining a distal resection depthbased on whether or not the most distal vertex is located on theosteophyte; and generating resection data using the distal resectiondepth, the resection data configured to be utilized by a navigationsystem during the arthroplasty procedure.
 19. The method of claim 18,wherein determining if the most distal vertex is located on anosteophyte comprises creating a second three-dimensional shapepositioned between the most distal vertex and the location.
 20. Themethod of claim 19, further comprises identifying particular vertices ofthe polygonal surface mesh that are enclosed by the secondthree-dimensional shape, and using information associated with theparticular vertices to determine if the distal vertex is located on anosteophyte.
 21. The method of claim 20, wherein the information is aminimum and a maximum value in a direction associated with a presence ofan osteophyte protruding from an articular surface.
 22. The method ofclaim 19, further comprises identifying particular vertices of thepolygonal surface mesh that are enclosed by the second three-dimensionalshape, and using a minimum vertex value of one of the particularvertices enclosed by the second three-dimensional shape in a certaincoordinate direction and a maximum vertex value of another one of theparticular vertices enclosed by the second three-dimensional shape inthe certain coordinate direction to determine if the distal vertex islocated on an osteophyte.
 23. The method of claim 22, further comprisingdetermining the difference between the maximum vertex value and theminimum vertex value, and using the difference to determine the presenceof an osteophyte.
 24. The method of claim 23, further comprising usingthe difference to determine whether to increase or decrease a size ofthe sphere.
 25. The method of claim 19, wherein the secondthree-dimensional shape comprises a sphere having a radius of about 2 mmand is centered 1 mm towards the location from the most distal vertex.26. The method of claim 25, further comprising identifying particularvertices of the polygonal surface mesh that are enclosed by a boundaryof the sphere, and determining a difference between a maximum vertexvalue of one of the particular vertices enclosed by the boundary in acertain coordinate direction and a minimum vertex value of another oneof the particular vertices enclosed by the boundary in the certaincoordinate direction.
 27. The method of claim 19, wherein the secondthree-dimensional shape comprises a sphere.
 28. The method of claim 18,wherein the first three-dimensional shape comprises an ellipsoid. 29.The method of claim 18, wherein the navigation system operates inconjunction with an autonomous robot or a surgeon-assisted device inperforming the arthroplasty procedure.
 30. A method of generatingresection plane data for use in planning an arthroplasty procedure on apatient bone, the method comprising: obtaining patient data associatedwith at least a portion of the patient bone; generating athree-dimensional patient bone model from the patient data, the patientbone model oriented in a three-dimensional coordinate system andcomprising a polygonal surface mesh; identifying a particular directionin the three-dimensional coordinate system associated with a resectionplane; identifying a location on the polygonal surface mesh; creating asurface at or near the location; identifying a particular vertex of allvertices of the polygonal surface mesh that extends furthest beyond thesurface in the particular direction; using the particular vertex as afactor for determining a particular resection depth; and generatingresection data using the particular resection depth, the particularresection data configured to be utilized by a navigation system duringthe arthroplasty procedure.
 31. The method of claim 30, wherein thesurface is a plane.
 32. The method of claim 30, wherein the surface is athree-dimensional shape.
 33. The method of claim 32, wherein thethree-dimensional shape is a sphere, ellipsoid, prism, or cube.
 34. Themethod of claim 30, further comprising identifying a first location of afirst posterior point on a first three-dimensional bone model; andmapping the first location on the first three-dimensional bone model tothe location on the three-dimensional patient bone model, wherein thefirst location is positionally correlated with the location.
 35. Themethod of claim 34, wherein the first three-dimensional bone model is ageneric bone model.
 36. The method of claim 30, wherein the surfacecomprises a sphere with a radius of about 7 mm.
 37. The method of claim36, wherein the radius is multiplied by a scaling factor.
 38. The methodof claim 37, wherein the scaling factor is one of a medial-lateral oranterior-posterior size difference between the three-dimensional patientbone model and a generic bone model.
 39. The method of claim 30, whereinthe navigation system operates in conjunction with an autonomous robotor a surgeon-assisted device in performing the arthroplasty procedure.